{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![](http://osloyi5le.bkt.clouddn.com/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0%E5%B7%A5%E7%A8%8B%E5%B8%88banner.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 医疗费用分析与建模预估-随机森林解决回归问题\n",
    ">张子豪 同济大学研究生\n",
    "\n",
    "作者： 寒小阳、助教-Choc"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 作业说明\n",
    "\n",
    "· 任务一：选出特征和标签（用作数据分析）\n",
    "\n",
    "· 任务二：选出实际建模时所用的特征与标签，并对数据进行标准化处理\n",
    "\n",
    "· 任务三：构建模型，并进行训练、测试和评估\n",
    "\n",
    "· 任务四：在新数据上进行预测"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 步骤 0：import 需要的工具库"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import warnings\n",
    "warnings.filterwarnings('ignore')\n",
    "import pandas as pd\n",
    "from matplotlib import pyplot as plt\n",
    "import seaborn as sns\n",
    "from sklearn.ensemble import RandomForestRegressor\n",
    "from sklearn.preprocessing import LabelEncoder, StandardScaler\n",
    "from sklearn.model_selection import train_test_split\n",
    "import numpy as np\n",
    "import sklearn.metrics"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 步骤 1：加载数据，并进行分析"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "_cell_guid": "b1076dfc-b9ad-4769-8c92-a6c4dae69d19",
    "_uuid": "8f2839f25d086af736a60e9eeb907d3b93b6e0e5",
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>age</th>\n",
       "      <th>bmi</th>\n",
       "      <th>children</th>\n",
       "      <th>charges</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>1338.000000</td>\n",
       "      <td>1338.000000</td>\n",
       "      <td>1338.000000</td>\n",
       "      <td>1338.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>39.207025</td>\n",
       "      <td>30.663397</td>\n",
       "      <td>1.094918</td>\n",
       "      <td>13270.422265</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>14.049960</td>\n",
       "      <td>6.098187</td>\n",
       "      <td>1.205493</td>\n",
       "      <td>12110.011237</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>18.000000</td>\n",
       "      <td>15.960000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1121.873900</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>27.000000</td>\n",
       "      <td>26.296250</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>4740.287150</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>39.000000</td>\n",
       "      <td>30.400000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>9382.033000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>51.000000</td>\n",
       "      <td>34.693750</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>16639.912515</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>64.000000</td>\n",
       "      <td>53.130000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>63770.428010</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               age          bmi     children       charges\n",
       "count  1338.000000  1338.000000  1338.000000   1338.000000\n",
       "mean     39.207025    30.663397     1.094918  13270.422265\n",
       "std      14.049960     6.098187     1.205493  12110.011237\n",
       "min      18.000000    15.960000     0.000000   1121.873900\n",
       "25%      27.000000    26.296250     0.000000   4740.287150\n",
       "50%      39.000000    30.400000     1.000000   9382.033000\n",
       "75%      51.000000    34.693750     2.000000  16639.912515\n",
       "max      64.000000    53.130000     5.000000  63770.428010"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv('./insurance.csv')\n",
    "#剔除缺失值\n",
    "df = df.dropna()\n",
    "#查看数据分布状况\n",
    "df.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>age</th>\n",
       "      <th>sex</th>\n",
       "      <th>bmi</th>\n",
       "      <th>children</th>\n",
       "      <th>smoker</th>\n",
       "      <th>region</th>\n",
       "      <th>charges</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>19</td>\n",
       "      <td>female</td>\n",
       "      <td>27.900</td>\n",
       "      <td>0</td>\n",
       "      <td>yes</td>\n",
       "      <td>southwest</td>\n",
       "      <td>16884.92400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>18</td>\n",
       "      <td>male</td>\n",
       "      <td>33.770</td>\n",
       "      <td>1</td>\n",
       "      <td>no</td>\n",
       "      <td>southeast</td>\n",
       "      <td>1725.55230</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>28</td>\n",
       "      <td>male</td>\n",
       "      <td>33.000</td>\n",
       "      <td>3</td>\n",
       "      <td>no</td>\n",
       "      <td>southeast</td>\n",
       "      <td>4449.46200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>33</td>\n",
       "      <td>male</td>\n",
       "      <td>22.705</td>\n",
       "      <td>0</td>\n",
       "      <td>no</td>\n",
       "      <td>northwest</td>\n",
       "      <td>21984.47061</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>32</td>\n",
       "      <td>male</td>\n",
       "      <td>28.880</td>\n",
       "      <td>0</td>\n",
       "      <td>no</td>\n",
       "      <td>northwest</td>\n",
       "      <td>3866.85520</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>31</td>\n",
       "      <td>female</td>\n",
       "      <td>25.740</td>\n",
       "      <td>0</td>\n",
       "      <td>no</td>\n",
       "      <td>southeast</td>\n",
       "      <td>3756.62160</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>46</td>\n",
       "      <td>female</td>\n",
       "      <td>33.440</td>\n",
       "      <td>1</td>\n",
       "      <td>no</td>\n",
       "      <td>southeast</td>\n",
       "      <td>8240.58960</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>37</td>\n",
       "      <td>female</td>\n",
       "      <td>27.740</td>\n",
       "      <td>3</td>\n",
       "      <td>no</td>\n",
       "      <td>northwest</td>\n",
       "      <td>7281.50560</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>37</td>\n",
       "      <td>male</td>\n",
       "      <td>29.830</td>\n",
       "      <td>2</td>\n",
       "      <td>no</td>\n",
       "      <td>northeast</td>\n",
       "      <td>6406.41070</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>60</td>\n",
       "      <td>female</td>\n",
       "      <td>25.840</td>\n",
       "      <td>0</td>\n",
       "      <td>no</td>\n",
       "      <td>northwest</td>\n",
       "      <td>28923.13692</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>25</td>\n",
       "      <td>male</td>\n",
       "      <td>26.220</td>\n",
       "      <td>0</td>\n",
       "      <td>no</td>\n",
       "      <td>northeast</td>\n",
       "      <td>2721.32080</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>62</td>\n",
       "      <td>female</td>\n",
       "      <td>26.290</td>\n",
       "      <td>0</td>\n",
       "      <td>yes</td>\n",
       "      <td>southeast</td>\n",
       "      <td>27808.72510</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>23</td>\n",
       "      <td>male</td>\n",
       "      <td>34.400</td>\n",
       "      <td>0</td>\n",
       "      <td>no</td>\n",
       "      <td>southwest</td>\n",
       "      <td>1826.84300</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>56</td>\n",
       "      <td>female</td>\n",
       "      <td>39.820</td>\n",
       "      <td>0</td>\n",
       "      <td>no</td>\n",
       "      <td>southeast</td>\n",
       "      <td>11090.71780</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>27</td>\n",
       "      <td>male</td>\n",
       "      <td>42.130</td>\n",
       "      <td>0</td>\n",
       "      <td>yes</td>\n",
       "      <td>southeast</td>\n",
       "      <td>39611.75770</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>19</td>\n",
       "      <td>male</td>\n",
       "      <td>24.600</td>\n",
       "      <td>1</td>\n",
       "      <td>no</td>\n",
       "      <td>southwest</td>\n",
       "      <td>1837.23700</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>52</td>\n",
       "      <td>female</td>\n",
       "      <td>30.780</td>\n",
       "      <td>1</td>\n",
       "      <td>no</td>\n",
       "      <td>northeast</td>\n",
       "      <td>10797.33620</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>23</td>\n",
       "      <td>male</td>\n",
       "      <td>23.845</td>\n",
       "      <td>0</td>\n",
       "      <td>no</td>\n",
       "      <td>northeast</td>\n",
       "      <td>2395.17155</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>56</td>\n",
       "      <td>male</td>\n",
       "      <td>40.300</td>\n",
       "      <td>0</td>\n",
       "      <td>no</td>\n",
       "      <td>southwest</td>\n",
       "      <td>10602.38500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>30</td>\n",
       "      <td>male</td>\n",
       "      <td>35.300</td>\n",
       "      <td>0</td>\n",
       "      <td>yes</td>\n",
       "      <td>southwest</td>\n",
       "      <td>36837.46700</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>60</td>\n",
       "      <td>female</td>\n",
       "      <td>36.005</td>\n",
       "      <td>0</td>\n",
       "      <td>no</td>\n",
       "      <td>northeast</td>\n",
       "      <td>13228.84695</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>30</td>\n",
       "      <td>female</td>\n",
       "      <td>32.400</td>\n",
       "      <td>1</td>\n",
       "      <td>no</td>\n",
       "      <td>southwest</td>\n",
       "      <td>4149.73600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>18</td>\n",
       "      <td>male</td>\n",
       "      <td>34.100</td>\n",
       "      <td>0</td>\n",
       "      <td>no</td>\n",
       "      <td>southeast</td>\n",
       "      <td>1137.01100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>34</td>\n",
       "      <td>female</td>\n",
       "      <td>31.920</td>\n",
       "      <td>1</td>\n",
       "      <td>yes</td>\n",
       "      <td>northeast</td>\n",
       "      <td>37701.87680</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>37</td>\n",
       "      <td>male</td>\n",
       "      <td>28.025</td>\n",
       "      <td>2</td>\n",
       "      <td>no</td>\n",
       "      <td>northwest</td>\n",
       "      <td>6203.90175</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>59</td>\n",
       "      <td>female</td>\n",
       "      <td>27.720</td>\n",
       "      <td>3</td>\n",
       "      <td>no</td>\n",
       "      <td>southeast</td>\n",
       "      <td>14001.13380</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>63</td>\n",
       "      <td>female</td>\n",
       "      <td>23.085</td>\n",
       "      <td>0</td>\n",
       "      <td>no</td>\n",
       "      <td>northeast</td>\n",
       "      <td>14451.83515</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>55</td>\n",
       "      <td>female</td>\n",
       "      <td>32.775</td>\n",
       "      <td>2</td>\n",
       "      <td>no</td>\n",
       "      <td>northwest</td>\n",
       "      <td>12268.63225</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>23</td>\n",
       "      <td>male</td>\n",
       "      <td>17.385</td>\n",
       "      <td>1</td>\n",
       "      <td>no</td>\n",
       "      <td>northwest</td>\n",
       "      <td>2775.19215</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>31</td>\n",
       "      <td>male</td>\n",
       "      <td>36.300</td>\n",
       "      <td>2</td>\n",
       "      <td>yes</td>\n",
       "      <td>southwest</td>\n",
       "      <td>38711.00000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1308</th>\n",
       "      <td>25</td>\n",
       "      <td>female</td>\n",
       "      <td>30.200</td>\n",
       "      <td>0</td>\n",
       "      <td>yes</td>\n",
       "      <td>southwest</td>\n",
       "      <td>33900.65300</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1309</th>\n",
       "      <td>41</td>\n",
       "      <td>male</td>\n",
       "      <td>32.200</td>\n",
       "      <td>2</td>\n",
       "      <td>no</td>\n",
       "      <td>southwest</td>\n",
       "      <td>6875.96100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1310</th>\n",
       "      <td>42</td>\n",
       "      <td>male</td>\n",
       "      <td>26.315</td>\n",
       "      <td>1</td>\n",
       "      <td>no</td>\n",
       "      <td>northwest</td>\n",
       "      <td>6940.90985</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1311</th>\n",
       "      <td>33</td>\n",
       "      <td>female</td>\n",
       "      <td>26.695</td>\n",
       "      <td>0</td>\n",
       "      <td>no</td>\n",
       "      <td>northwest</td>\n",
       "      <td>4571.41305</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1312</th>\n",
       "      <td>34</td>\n",
       "      <td>male</td>\n",
       "      <td>42.900</td>\n",
       "      <td>1</td>\n",
       "      <td>no</td>\n",
       "      <td>southwest</td>\n",
       "      <td>4536.25900</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1313</th>\n",
       "      <td>19</td>\n",
       "      <td>female</td>\n",
       "      <td>34.700</td>\n",
       "      <td>2</td>\n",
       "      <td>yes</td>\n",
       "      <td>southwest</td>\n",
       "      <td>36397.57600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1314</th>\n",
       "      <td>30</td>\n",
       "      <td>female</td>\n",
       "      <td>23.655</td>\n",
       "      <td>3</td>\n",
       "      <td>yes</td>\n",
       "      <td>northwest</td>\n",
       "      <td>18765.87545</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1315</th>\n",
       "      <td>18</td>\n",
       "      <td>male</td>\n",
       "      <td>28.310</td>\n",
       "      <td>1</td>\n",
       "      <td>no</td>\n",
       "      <td>northeast</td>\n",
       "      <td>11272.33139</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1316</th>\n",
       "      <td>19</td>\n",
       "      <td>female</td>\n",
       "      <td>20.600</td>\n",
       "      <td>0</td>\n",
       "      <td>no</td>\n",
       "      <td>southwest</td>\n",
       "      <td>1731.67700</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1317</th>\n",
       "      <td>18</td>\n",
       "      <td>male</td>\n",
       "      <td>53.130</td>\n",
       "      <td>0</td>\n",
       "      <td>no</td>\n",
       "      <td>southeast</td>\n",
       "      <td>1163.46270</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1318</th>\n",
       "      <td>35</td>\n",
       "      <td>male</td>\n",
       "      <td>39.710</td>\n",
       "      <td>4</td>\n",
       "      <td>no</td>\n",
       "      <td>northeast</td>\n",
       "      <td>19496.71917</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1319</th>\n",
       "      <td>39</td>\n",
       "      <td>female</td>\n",
       "      <td>26.315</td>\n",
       "      <td>2</td>\n",
       "      <td>no</td>\n",
       "      <td>northwest</td>\n",
       "      <td>7201.70085</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1320</th>\n",
       "      <td>31</td>\n",
       "      <td>male</td>\n",
       "      <td>31.065</td>\n",
       "      <td>3</td>\n",
       "      <td>no</td>\n",
       "      <td>northwest</td>\n",
       "      <td>5425.02335</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1321</th>\n",
       "      <td>62</td>\n",
       "      <td>male</td>\n",
       "      <td>26.695</td>\n",
       "      <td>0</td>\n",
       "      <td>yes</td>\n",
       "      <td>northeast</td>\n",
       "      <td>28101.33305</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1322</th>\n",
       "      <td>62</td>\n",
       "      <td>male</td>\n",
       "      <td>38.830</td>\n",
       "      <td>0</td>\n",
       "      <td>no</td>\n",
       "      <td>southeast</td>\n",
       "      <td>12981.34570</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1323</th>\n",
       "      <td>42</td>\n",
       "      <td>female</td>\n",
       "      <td>40.370</td>\n",
       "      <td>2</td>\n",
       "      <td>yes</td>\n",
       "      <td>southeast</td>\n",
       "      <td>43896.37630</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1324</th>\n",
       "      <td>31</td>\n",
       "      <td>male</td>\n",
       "      <td>25.935</td>\n",
       "      <td>1</td>\n",
       "      <td>no</td>\n",
       "      <td>northwest</td>\n",
       "      <td>4239.89265</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1325</th>\n",
       "      <td>61</td>\n",
       "      <td>male</td>\n",
       "      <td>33.535</td>\n",
       "      <td>0</td>\n",
       "      <td>no</td>\n",
       "      <td>northeast</td>\n",
       "      <td>13143.33665</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1326</th>\n",
       "      <td>42</td>\n",
       "      <td>female</td>\n",
       "      <td>32.870</td>\n",
       "      <td>0</td>\n",
       "      <td>no</td>\n",
       "      <td>northeast</td>\n",
       "      <td>7050.02130</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1327</th>\n",
       "      <td>51</td>\n",
       "      <td>male</td>\n",
       "      <td>30.030</td>\n",
       "      <td>1</td>\n",
       "      <td>no</td>\n",
       "      <td>southeast</td>\n",
       "      <td>9377.90470</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1328</th>\n",
       "      <td>23</td>\n",
       "      <td>female</td>\n",
       "      <td>24.225</td>\n",
       "      <td>2</td>\n",
       "      <td>no</td>\n",
       "      <td>northeast</td>\n",
       "      <td>22395.74424</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1329</th>\n",
       "      <td>52</td>\n",
       "      <td>male</td>\n",
       "      <td>38.600</td>\n",
       "      <td>2</td>\n",
       "      <td>no</td>\n",
       "      <td>southwest</td>\n",
       "      <td>10325.20600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1330</th>\n",
       "      <td>57</td>\n",
       "      <td>female</td>\n",
       "      <td>25.740</td>\n",
       "      <td>2</td>\n",
       "      <td>no</td>\n",
       "      <td>southeast</td>\n",
       "      <td>12629.16560</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1331</th>\n",
       "      <td>23</td>\n",
       "      <td>female</td>\n",
       "      <td>33.400</td>\n",
       "      <td>0</td>\n",
       "      <td>no</td>\n",
       "      <td>southwest</td>\n",
       "      <td>10795.93733</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1332</th>\n",
       "      <td>52</td>\n",
       "      <td>female</td>\n",
       "      <td>44.700</td>\n",
       "      <td>3</td>\n",
       "      <td>no</td>\n",
       "      <td>southwest</td>\n",
       "      <td>11411.68500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1333</th>\n",
       "      <td>50</td>\n",
       "      <td>male</td>\n",
       "      <td>30.970</td>\n",
       "      <td>3</td>\n",
       "      <td>no</td>\n",
       "      <td>northwest</td>\n",
       "      <td>10600.54830</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1334</th>\n",
       "      <td>18</td>\n",
       "      <td>female</td>\n",
       "      <td>31.920</td>\n",
       "      <td>0</td>\n",
       "      <td>no</td>\n",
       "      <td>northeast</td>\n",
       "      <td>2205.98080</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1335</th>\n",
       "      <td>18</td>\n",
       "      <td>female</td>\n",
       "      <td>36.850</td>\n",
       "      <td>0</td>\n",
       "      <td>no</td>\n",
       "      <td>southeast</td>\n",
       "      <td>1629.83350</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1336</th>\n",
       "      <td>21</td>\n",
       "      <td>female</td>\n",
       "      <td>25.800</td>\n",
       "      <td>0</td>\n",
       "      <td>no</td>\n",
       "      <td>southwest</td>\n",
       "      <td>2007.94500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1337</th>\n",
       "      <td>61</td>\n",
       "      <td>female</td>\n",
       "      <td>29.070</td>\n",
       "      <td>0</td>\n",
       "      <td>yes</td>\n",
       "      <td>northwest</td>\n",
       "      <td>29141.36030</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1338 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      age     sex     bmi  children smoker     region      charges\n",
       "0      19  female  27.900         0    yes  southwest  16884.92400\n",
       "1      18    male  33.770         1     no  southeast   1725.55230\n",
       "2      28    male  33.000         3     no  southeast   4449.46200\n",
       "3      33    male  22.705         0     no  northwest  21984.47061\n",
       "4      32    male  28.880         0     no  northwest   3866.85520\n",
       "5      31  female  25.740         0     no  southeast   3756.62160\n",
       "6      46  female  33.440         1     no  southeast   8240.58960\n",
       "7      37  female  27.740         3     no  northwest   7281.50560\n",
       "8      37    male  29.830         2     no  northeast   6406.41070\n",
       "9      60  female  25.840         0     no  northwest  28923.13692\n",
       "10     25    male  26.220         0     no  northeast   2721.32080\n",
       "11     62  female  26.290         0    yes  southeast  27808.72510\n",
       "12     23    male  34.400         0     no  southwest   1826.84300\n",
       "13     56  female  39.820         0     no  southeast  11090.71780\n",
       "14     27    male  42.130         0    yes  southeast  39611.75770\n",
       "15     19    male  24.600         1     no  southwest   1837.23700\n",
       "16     52  female  30.780         1     no  northeast  10797.33620\n",
       "17     23    male  23.845         0     no  northeast   2395.17155\n",
       "18     56    male  40.300         0     no  southwest  10602.38500\n",
       "19     30    male  35.300         0    yes  southwest  36837.46700\n",
       "20     60  female  36.005         0     no  northeast  13228.84695\n",
       "21     30  female  32.400         1     no  southwest   4149.73600\n",
       "22     18    male  34.100         0     no  southeast   1137.01100\n",
       "23     34  female  31.920         1    yes  northeast  37701.87680\n",
       "24     37    male  28.025         2     no  northwest   6203.90175\n",
       "25     59  female  27.720         3     no  southeast  14001.13380\n",
       "26     63  female  23.085         0     no  northeast  14451.83515\n",
       "27     55  female  32.775         2     no  northwest  12268.63225\n",
       "28     23    male  17.385         1     no  northwest   2775.19215\n",
       "29     31    male  36.300         2    yes  southwest  38711.00000\n",
       "...   ...     ...     ...       ...    ...        ...          ...\n",
       "1308   25  female  30.200         0    yes  southwest  33900.65300\n",
       "1309   41    male  32.200         2     no  southwest   6875.96100\n",
       "1310   42    male  26.315         1     no  northwest   6940.90985\n",
       "1311   33  female  26.695         0     no  northwest   4571.41305\n",
       "1312   34    male  42.900         1     no  southwest   4536.25900\n",
       "1313   19  female  34.700         2    yes  southwest  36397.57600\n",
       "1314   30  female  23.655         3    yes  northwest  18765.87545\n",
       "1315   18    male  28.310         1     no  northeast  11272.33139\n",
       "1316   19  female  20.600         0     no  southwest   1731.67700\n",
       "1317   18    male  53.130         0     no  southeast   1163.46270\n",
       "1318   35    male  39.710         4     no  northeast  19496.71917\n",
       "1319   39  female  26.315         2     no  northwest   7201.70085\n",
       "1320   31    male  31.065         3     no  northwest   5425.02335\n",
       "1321   62    male  26.695         0    yes  northeast  28101.33305\n",
       "1322   62    male  38.830         0     no  southeast  12981.34570\n",
       "1323   42  female  40.370         2    yes  southeast  43896.37630\n",
       "1324   31    male  25.935         1     no  northwest   4239.89265\n",
       "1325   61    male  33.535         0     no  northeast  13143.33665\n",
       "1326   42  female  32.870         0     no  northeast   7050.02130\n",
       "1327   51    male  30.030         1     no  southeast   9377.90470\n",
       "1328   23  female  24.225         2     no  northeast  22395.74424\n",
       "1329   52    male  38.600         2     no  southwest  10325.20600\n",
       "1330   57  female  25.740         2     no  southeast  12629.16560\n",
       "1331   23  female  33.400         0     no  southwest  10795.93733\n",
       "1332   52  female  44.700         3     no  southwest  11411.68500\n",
       "1333   50    male  30.970         3     no  northwest  10600.54830\n",
       "1334   18  female  31.920         0     no  northeast   2205.98080\n",
       "1335   18  female  36.850         0     no  southeast   1629.83350\n",
       "1336   21  female  25.800         0     no  southwest   2007.94500\n",
       "1337   61  female  29.070         0    yes  northwest  29141.36030\n",
       "\n",
       "[1338 rows x 7 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "_uuid": "dc9600cade1f721de52c0b5be3bf096e7efd75b1"
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>age</th>\n",
       "      <th>bmi</th>\n",
       "      <th>children</th>\n",
       "      <th>charges</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>age</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.109272</td>\n",
       "      <td>0.042469</td>\n",
       "      <td>0.299008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>bmi</th>\n",
       "      <td>0.109272</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.012759</td>\n",
       "      <td>0.198341</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>children</th>\n",
       "      <td>0.042469</td>\n",
       "      <td>0.012759</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.067998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>charges</th>\n",
       "      <td>0.299008</td>\n",
       "      <td>0.198341</td>\n",
       "      <td>0.067998</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               age       bmi  children   charges\n",
       "age       1.000000  0.109272  0.042469  0.299008\n",
       "bmi       0.109272  1.000000  0.012759  0.198341\n",
       "children  0.042469  0.012759  1.000000  0.067998\n",
       "charges   0.299008  0.198341  0.067998  1.000000"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#查看不同维度之间的相关性\n",
    "df.corr()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### **任务一：选出特征和标签（用作数据分析）**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "df = df.sort_values(by=[\"age\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "18    69\n",
       "19    68\n",
       "51    29\n",
       "45    29\n",
       "46    29\n",
       "47    29\n",
       "48    29\n",
       "50    29\n",
       "52    29\n",
       "20    29\n",
       "26    28\n",
       "54    28\n",
       "53    28\n",
       "25    28\n",
       "24    28\n",
       "49    28\n",
       "23    28\n",
       "22    28\n",
       "21    28\n",
       "27    28\n",
       "28    28\n",
       "31    27\n",
       "29    27\n",
       "30    27\n",
       "41    27\n",
       "43    27\n",
       "44    27\n",
       "40    27\n",
       "42    27\n",
       "57    26\n",
       "34    26\n",
       "33    26\n",
       "32    26\n",
       "56    26\n",
       "55    26\n",
       "59    25\n",
       "58    25\n",
       "39    25\n",
       "38    25\n",
       "35    25\n",
       "36    25\n",
       "37    25\n",
       "63    23\n",
       "60    23\n",
       "61    23\n",
       "62    23\n",
       "64    22\n",
       "Name: age, dtype: int64"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[\"age\"].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXQAAAD/CAYAAADhYy38AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMi4zLCBo\ndHRwOi8vbWF0cGxvdGxpYi5vcmcvIxREBQAAF6JJREFUeJzt3X20XXV95/H3FyLWh8pDuA0MiKHy\nJDMs0N4GHWBUIi6ULkkdhsp0XJHBSTv1sWWqseOM6Lha6Ey1zmpLF+WhUWuBojQUWysGHLUtSIAA\nQsCECBUk5IogFMLzd/7YvxtOTs7Z5+Hem4Tfer/WOuvss397799v7/3bn7PPPvvcG5mJJOmFb5cd\n3QBJ0uww0CWpEga6JFXCQJekShjoklQJA12SKmGgS1IlDHRJqoSBLkmVMNAlqRLztmdle++9dy5c\nuHB7VilJL3g33HDDjzNzYtB02zXQFy5cyOrVq7dnlZL0ghcR9wwznZdcJKkSAwM9Ig6NiDUdj0ci\n4sMRsVdEXBUR68rzntujwZKk3gYGembemZlHZeZRwC8AjwOXA8uBVZl5MLCqvJYk7SCjXnJZDNyV\nmfcAJwMryvgVwJLZbJgkaTSjBvq7gL8swwsy8/4yvBFYMGutkiSNbOhAj4jdgHcAf9Vdls2/Per5\nr48iYllErI6I1VNTU2M3VJLUbpQz9LcBN2bmA+X1AxGxL0B53tRrpsw8LzMnM3NyYmLgbZSSpDGN\nEuin8fzlFoArgKVleCmwcrYaJUka3VA/LIqIlwEnAL/WMfps4NKIOAO4Bzh12EoXLv/qluG7zz5p\n2NkkSS2GCvTMfAyY3zXuQZq7XiRJOwF/KSpJldiuf8tlKGft3jH80x3XDkl6gfEMXZIqYaBLUiUM\ndEmqhIEuSZUw0CWpEga6JFXCQJekShjoklQJA12SKmGgS1IlDHRJqoSBLkmVMNAlqRIGuiRVwkCX\npEoY6JJUCQNdkiphoEtSJQx0SarEUIEeEXtExGURcUdErI2IN0TEXhFxVUSsK897znVjJUn9DXuG\n/jnga5l5GHAksBZYDqzKzIOBVeW1JGkHGRjoEbE78O+ACwAy86nMfBg4GVhRJlsBLJmrRkqSBhvm\nDP1AYAq4KCJuiojzI+JlwILMvL9MsxFYMFeNlCQNNkygzwNeB5ybma8FHqPr8kpmJpC9Zo6IZRGx\nOiJWT01NzbS9kqQ+hgn0e4F7M/O68voymoB/ICL2BSjPm3rNnJnnZeZkZk5OTEzMRpslST0MDPTM\n3Aj8MCIOLaMWA7cDVwBLy7ilwMo5aaEkaSjzhpzuA8BfRMRuwAbgdJo3g0sj4gzgHuDUuWmiJGkY\nQwV6Zq4BJnsULZ7d5kiSxuUvRSWpEga6JFXCQJekShjoklQJA12SKmGgS1IlDHRJqoSBLkmVMNAl\nqRIGuiRVwkCXpEoY6JJUCQNdkiphoEtSJQx0SaqEgS5JlTDQJakSBrokVcJAl6RKGOiSVAkDXZIq\nMW+YiSLibuBR4FngmcycjIi9gEuAhcDdwKmZ+dDcNFOSNMgoZ+hvzsyjMnOyvF4OrMrMg4FV5bUk\naQeZySWXk4EVZXgFsGTmzZEkjWvYQE/g6xFxQ0QsK+MWZOb9ZXgjsGDWWydJGtpQ19CBYzPzvoj4\nOeCqiLijszAzMyKy14zlDWAZwAEHHDCjxkqS+hvqDD0z7yvPm4DLgUXAAxGxL0B53tRn3vMyczIz\nJycmJman1ZKkbQwM9Ih4WUT87PQw8Fbge8AVwNIy2VJg5Vw1UpI02DCXXBYAl0fE9PRfysyvRcT1\nwKURcQZwD3Dq3DVTkjTIwEDPzA3AkT3GPwgsnotGSZJG5y9FJakSBrokVcJAl6RKGOiSVAkDXZIq\nYaBLUiUMdEmqhIEuSZUw0CWpEga6JFXCQJekShjoklQJA12SKmGgS1IlDHRJqoSBLkmVMNAlqRIG\nuiRVwkCXpEoY6JJUCQNdkioxdKBHxK4RcVNEXFleHxgR10XE+oi4JCJ2m7tmSpIGGeUM/UPA2o7X\n5wCfzcyDgIeAM2azYZKk0QwV6BGxP3AScH55HcDxwGVlkhXAkrlooCRpOMOeof8h8BHgufJ6PvBw\nZj5TXt8L7DfLbZMkjWBgoEfELwGbMvOGcSqIiGURsToiVk9NTY2zCEnSEIY5Qz8GeEdE3A1cTHOp\n5XPAHhExr0yzP3Bfr5kz87zMnMzMyYmJiVlosiSpl4GBnpkfy8z9M3Mh8C7g6sz8VeAa4JQy2VJg\n5Zy1UpI00EzuQ/8o8FsRsZ7mmvoFs9MkSdI45g2e5HmZ+U3gm2V4A7Bo9pskSRqHvxSVpEoY6JJU\nCQNdkiphoEtSJQx0SaqEgS5JlTDQJakSBrokVcJAl6RKGOiSVAkDXZIqYaBLUiUMdEmqhIEuSZUw\n0CWpEga6JFXCQJekShjoklQJA12SKmGgS1IlDHRJqsTAQI+In4mI70bEzRFxW0R8sow/MCKui4j1\nEXFJROw2982VJPUzzBn6k8DxmXkkcBRwYkS8HjgH+GxmHgQ8BJwxd82UJA0yMNCz8S/l5YvKI4Hj\ngcvK+BXAkjlpoSRpKENdQ4+IXSNiDbAJuAq4C3g4M58pk9wL7Dc3TZQkDWOoQM/MZzPzKGB/YBFw\n2LAVRMSyiFgdEaunpqbGbKYkaZCR7nLJzIeBa4A3AHtExLxStD9wX595zsvMycycnJiYmFFjJUn9\nDXOXy0RE7FGGXwKcAKylCfZTymRLgZVz1UhJ0mDzBk/CvsCKiNiV5g3g0sy8MiJuBy6OiE8DNwEX\nzGE7AThixRFbhm9deutWZWsPe81Wr19zx9otw3/861dvVfa+Pz1+y/Af/MovbVV25iVXbhm+d/m3\ntyrb/+zjtgyfddZZW5V1v1519au3DC8+/q6tyva5Zs2W4Y1vPgpJmg0DAz0zbwFe22P8Bprr6ZKk\nnYC/FJWkSgxzyUXb0cLlX90yfPfZJ/Ut26b8rN23XtBZP90y2HmpCra+XDXupSrY+nJV56Uq2Ppy\nVeelKtj68lTbpSrY+nJV56Uq8HKV1M0zdEmqhIEuSZXwkouq0HY5atxLVTD8nVWdl6pg68tV416q\ngm0vV0ltPEOXpEoY6JJUCS+5SC8QbT9mm8ndQcPeWdVdttXlqq5LVdoxPEOXpEoY6JJUCS+5SJp1\nO9PfXYLhf8zW/XeXXmg8Q5ekShjoklQJA12SKmGgS1IlDHRJqoR3uUhSH23/XWwu/tT1THmGLkmV\nMNAlqRJecpGknUTbfxcbhmfoklSJgYEeEa+MiGsi4vaIuC0iPlTG7xURV0XEuvK859w3V5LUzzBn\n6M8AZ2bm4cDrgfdFxOHAcmBVZh4MrCqvJUk7yMBAz8z7M/PGMvwosBbYDzgZWFEmWwEsmatGSpIG\nG+kaekQsBF4LXAcsyMz7S9FGYMGstkySNJKhAz0iXg58GfhwZj7SWZaZCWSf+ZZFxOqIWD01NTWj\nxkqS+hsq0CPiRTRh/heZ+ZUy+oGI2LeU7wts6jVvZp6XmZOZOTkxMTEbbZYk9TDMXS4BXACszczP\ndBRdASwtw0uBlbPfPEnSsIb5YdExwLuBWyNi+g8b/A5wNnBpRJwB3AOcOjdNlCQNY2CgZ+Z3gOhT\nvHh2myNJGpe/FJWkShjoklQJA12SKmGgS1IlDHRJqoSBLkmVMNAlqRIGuiRVwkCXpEoY6JJUCQNd\nkiphoEtSJQx0SaqEgS5JlTDQJakSBrokVcJAl6RKGOiSVAkDXZIqYaBLUiUMdEmqxMBAj4gLI2JT\nRHyvY9xeEXFVRKwrz3vObTMlSYMMc4b+58CJXeOWA6sy82BgVXktSdqBBgZ6Zn4L+EnX6JOBFWV4\nBbBkltslSRrRuNfQF2Tm/WV4I7BgltojSRrTjL8UzcwEsl95RCyLiNURsXpqamqm1UmS+hg30B+I\niH0ByvOmfhNm5nmZOZmZkxMTE2NWJ0kaZNxAvwJYWoaXAitnpzmSpHENc9viXwL/BBwaEfdGxBnA\n2cAJEbEOeEt5LUnageYNmiAzT+tTtHiW2yJJmgF/KSpJlTDQJakSBrokVcJAl6RKGOiSVAkDXZIq\nYaBLUiUMdEmqhIEuSZUw0CWpEga6JFXCQJekShjoklQJA12SKmGgS1IlDHRJqoSBLkmVMNAlqRIG\nuiRVwkCXpEoY6JJUiRkFekScGBF3RsT6iFg+W42SJI1u7ECPiF2BPwbeBhwOnBYRh89WwyRJo5nJ\nGfoiYH1mbsjMp4CLgZNnp1mSpFHNJND3A37Y8freMk6StANEZo43Y8QpwImZ+d7y+t3A0Zn5/q7p\nlgHLystDgTvL8N7Aj1uqaCuvvWxna4/r6Dq6jju2Pa/KzImW9jUyc6wH8Abg7ztefwz42Ajzrx63\nvPayna09rqPr6DruXO3p95jJJZfrgYMj4sCI2A14F3DFDJYnSZqBeePOmJnPRMT7gb8HdgUuzMzb\nZq1lkqSRjB3oAJn5t8Dfjjn7eTMor71sR9TpOs5+2Y6o03Wc/bIdUeeg9vQ09peikqSdiz/9l6RK\nGOiSVAkDXZIqYaDvhCJi/oDyn5uDOmd9marDoP6o2Tf28TjOzes7wwP4Tsfwi4CP09wH/7vAbwJ7\nl7KDgG8BDwPXAd8A/hPw8j7L/XngQuDTwMuBPwO+B/wVcARwNnAH8BPgQWBtGfdK4PeALwD/sWuZ\n57fM99mOtk4CG4D1wD3AG4G9uh7zgbuBPYHDgHNp/kjafOAs4FbgUuC0jvp3By4AbgG+RPOL3X7L\nnA/8Z+CrwM3AjTR/p+dNwD4t9R3csv5/0rIff1r23av7lE8C1wBfLNv4qjLP9cBrW5Z7IfAp4LYy\n/RRwLfAemru7fg34WtkmtwB/B/w68KKWZV4AfAT4beBnyrKuAH6/V38Cvl+e2+p7cSn7X8AxXfN/\nvGz/vtunpc6XtrT1FS11fov+/fG3W/rUAprjpd82b9uPr2vpc23H44mznQG09/FD6H8c7zFgv3yd\n/sfHBfQ/HvcaKRe3YwC37dB/26cjfKLs7O7HLwBPdyz7D4A/pwnAzwIPd5R9FfjlMvwm4EngsrJD\nLgV+Gditq0P/V2B56ThnlvaeUXbgR4F9ujrAR4EHyo5dUjrVl4EXl2keaZnv0Y5x1wC/WIYPAVYD\nzwE/6Ho8XZ4fBz5Q2npLWd4ry7jObXA+zQHxKpqOni3LfJSmEx8L/GHZLyfQHAS3t9T3o5b1X9uy\nH58B/g/wz8B3S/v+VUfbv0vzFz1Po/nbQaeU8Ytp+k73G970AbGZJkj2B34L+B80bzoraPrZucDr\nS/n+Zfhc4PKWZT5O09f+BFgF/BFwHPC/y/Z7pDweLY9ny/PTLfVtoAnEDwM3AJ/pWPcbyz7puX3K\nstvq7NfWdS11bm7pj4+19Km/Bla2bPMftezHTfTvc+vpfzw+OtsZQPOm26+Pb6L/cfx1evfx6X6+\nmf7HR9vxuGFnDfS2A/MnfTrCczTvVNf0eDzXsew1lDMrIIAnOsqu72rH5vL8CuDdNPfRTwEXAW8F\nbuqY9p+75n2iZf2e6Hr934F/oAmCtvmeBOaV4Wu7ym4tHfhrwBEd439Qntva+njn9ukqu69lmbd0\nTXtteX5x13btrm9z1+vO9U/g6iH243E0AbSxlC0bsI5JE4idB8L06+e6pr2+PO8CPNWyPwYus/Sx\njTx/22/Q/N2NzwMLemzT77ft/47heTT3H3+lbO+bgBtbts+qljrXtLR1c0udT7T0x875uvvUGuDm\nlm0+St8Zts893lX/bGTA+pb62o7jO2neTAf28x7Hx730OR5HfWzPQG87MLt36HRH+B5wV5/lPUPz\nzvrvgbVdZQ/QvFv/PPA7NGcirwJOB37aY1nzaT7+Xk1zxnII8Is0B+lkmeYgmjOfj3QdQAto3qEf\nA3bpWu57aM4GN7fMdwfNu/vxNGcpn6M5y/gk8IUy7f40HzE/A/ws5V2bjgMI+HRX3U/RvDmeSRNI\n0VF2S8syb6B8vKc5u/hWrw7do74nWtb/KeDgPvtxm3Cl+eXxiTQH2D/RvNH+B5qP/UvKNG8sdR7Q\nZ7lPAseW4Xew9d8d2lyWt0vHuF2AXxmwzKc6hi/sKruZ5kzsauCDZXnT2/Talvo296jnEzQH+zo6\nAr3P9ulX55qWtm4TTB11bmrpj48N6FP/OGCb99uPj7X0uc00x+Mitj0enwTeyexmQOdZf3cfbzv+\nv0GTV/36+dP0Pz7uoc/xOOpjewZ624H5L706AnBKvxUrnfiijseCMn4fmjOX02mul/247Ijbaa6t\n/cOAdi6mebddS/MR8Ms0B9Ym4FeBc2hC+CGaTxZry7j/C7ylx/JOBO5qmW8vmo+Bl9Cckd1Kc8aw\njK7ruWXbXAtsLK8/Re/rgAeVjvKJjsdEx/b5fMsyj6f5eL+e5qz09WX8BM0B36++O1vW/37g0D7b\n+9sD9seRNH9e4u9ovjP4HM210NtoLkUc2We+36P5VPgQ8J3p+st6nFW29ybg++WxqYz7ny3L/Mc+\n6/9qync6NKH6QeDbwI/KuIVl2VOlrnUd9V1Ox7XgjmW+lyYELh7i2OpV5/ktbd00oM5+/fGTbX2q\n7KvObX5IxzY/p8d+fKjsxw+UPreu9LmjO+a7mP7H4zdoz4D3MGIG0H5MraT9OD6F/v38K/Q/Ptb1\nOx5HfWzPQG87MN/d0hE+2LGMY2nOEN7ap47Pt9T/hZayvvOV8ivpenct44+jOVvZpj3dbS3r/Jbu\nzlJ26GE0byTblPWp8+Mj1NlzuZ1lwEuAf9NRFpQvlLq3z7DL7Cp725jznVieX9My7yKev857eFn/\nt3fM12+bH13mnQ8cA/y36flG7FefL8/RNX5f4MEe088vjy+O0x977OPO9T+O5g3p7T3KprfNSWX/\n9t1u4/bxUcq7l0vz11v77cejO8r+dee+6irrnm9R13xnDtg2by/Le0UZ/xKaN7G/oQnt44HdS9lL\nacL/ylK2e495P9Vn3l5lr+hY7u/TvFmdMz3PsI+d4qf/EXF6Zl7UY/x3gXMz86KI+C/A+2jOaN5K\n8w3w+q5Zjqc5c19E8wYxTFkAby5l/UzPe1xm7lna9t7Snr8u7TkgM19Zyrrb+iDNnSVrgaOAD2Xm\nyjLtD2m+bOtVdiPwTGYu6ljubwxZ549pgnLUOh+m+WK41/ofCOw2xjLHLbuR5mPzb9CcFXWX/4jm\nzG4ezZfsR9NcrzyB5ovCg4acbxHwzTLfBM0Z4LTO/tHWd0bpc21l3f1xn67937mPH6f5eN5rPZ6i\nebPutW3ayg7s6FNtffy9wPs72vI3wDs72tpd3t1XO/vxKOsxF2Wd638osF82f3zwvNK2y2hOKM6k\nuetkuuwxmk8Mi2lOWA+l+XQ3zLxDLzcz38mwRkn/uXrQdU29Y/xN02U0dzRMf8R7Gc21tS/SfDx8\nY3m+vwx/v6VsXUvZG0udfeftaNs27Wkpe4Jylkjz8Xs1TcBQ1qNf2U1s/d3D9qjz8Zb13zDmMsct\nm/7I3zbvrjRnNY+w9dnRoDrb5hun77T1uRn1xwH7uG09xiobs7/dOqCtg/rqrK/HmGWd3xNt9f3F\ngLI1dFzHH3He1uWOlKXbMbRv6fO4leZull5lm2m++JhP1x98pznYf5PmHfaoMm76C6FdxikbYt6b\nef5e7e72bG4r63r9cppvtT8zoGzNDqqz3/rfNuYyZ9KWtjo773K4aYT1b5uvbf3H6lfjlg3R59rW\nY9yy1j7VUnbTgLa2zTsX6zFu2cPA6WX4Ip7/EvYQmmvm/cqup/lSc5x5W5fb2b5Bj+0Z6A/QfPR9\nVddjIc3tPr3K7qW5m+UHNGeH+3YcnNO3ZU1/O/xHbHv3zFhl/cppbqHc0Kc9T7WUPUo5WDuWP4/m\ni6RsKXt2R9TZsv5Xj7nMccueHaLOl5ZxnXeQ7D7E+veb78a56lfjlA3Y/4+1rMe4ZU+O2d/WDGhr\n27xzsR7jlq2hucx3F80Xqk+X9v4/mu9a+pUdWeYfZ97W5Y6Us7MV2AMran4NdWyfsrtayr7UY9xL\naa71dY47CfjdPssYq2yY8n7t6Sp7Ax0/RugqX9JSdsyOrrNz/WlCZ5xljlt2zIA639Rn/N40X4aO\nM98RXeNmvV/NpD927eN+d1TsDbxuzLIjWupr6289y4acdy7WY0brT3OP+pE0t4Uu6Jqub9lM5h20\n3GEeO8WXopKkmfOPc0lSJQx0SaqEgS5JlTDQJakSBrokVeL/A9XaJle6RAcbAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df[\"age\"].value_counts().plot(kind = 'bar')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "_cell_guid": "79c7e3d0-c299-4dcb-8224-4455121ee9b0",
    "_uuid": "d629ff2d2480ee46fbb7e2d37f6b5fab8052498a"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "数据分布分析：\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXQAAAELCAYAAADJF31HAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXoAAAEhCAYAAABx6WukAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nzqCXpM4Z9JLUOYNekjr3/wBVTs8DxE6FfwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXQAAAELCAYAAADJF31HAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXoAAAEFCAYAAADt1CyEAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYAAAAEQCAYAAAC5oaP8AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXoAAAEyCAYAAAD0qxuRAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\ncEZsGzgAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 注：bmi（Body Mass Index）为身体质量指数，这里省略小数点来区间化特征，方便做数据分析\n",
    "df['bmi_int'] = df['bmi'].apply(lambda x: int(x))\n",
    "\n",
    "# 提示：可使用head函数查看列表；根据主题 医疗费用分析 选出特征\n",
    "variables = [\"age\",\"sex\",\"bmi_int\",\"children\",\"smoker\",\"region\"]                  # YOUR CODE HERE \n",
    "\n",
    "# 数据分布分析\n",
    "print('数据分布分析：')\n",
    "for v in variables:\n",
    "    df = df.sort_values(by=[v])\n",
    "    df[v].value_counts().plot(kind = 'bar')\n",
    "    plt.title(v)\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>age</th>\n",
       "      <th>sex</th>\n",
       "      <th>bmi</th>\n",
       "      <th>children</th>\n",
       "      <th>smoker</th>\n",
       "      <th>region</th>\n",
       "      <th>charges</th>\n",
       "      <th>bmi_int</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>172</th>\n",
       "      <td>18</td>\n",
       "      <td>male</td>\n",
       "      <td>15.960</td>\n",
       "      <td>0</td>\n",
       "      <td>no</td>\n",
       "      <td>northeast</td>\n",
       "      <td>1694.796400</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>161</th>\n",
       "      <td>18</td>\n",
       "      <td>female</td>\n",
       "      <td>36.850</td>\n",
       "      <td>0</td>\n",
       "      <td>yes</td>\n",
       "      <td>southeast</td>\n",
       "      <td>36149.483500</td>\n",
       "      <td>36</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1317</th>\n",
       "      <td>18</td>\n",
       "      <td>male</td>\n",
       "      <td>53.130</td>\n",
       "      <td>0</td>\n",
       "      <td>no</td>\n",
       "      <td>southeast</td>\n",
       "      <td>1163.462700</td>\n",
       "      <td>53</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>940</th>\n",
       "      <td>18</td>\n",
       "      <td>male</td>\n",
       "      <td>23.210</td>\n",
       "      <td>0</td>\n",
       "      <td>no</td>\n",
       "      <td>southeast</td>\n",
       "      <td>1121.873900</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>803</th>\n",
       "      <td>18</td>\n",
       "      <td>female</td>\n",
       "      <td>42.240</td>\n",
       "      <td>0</td>\n",
       "      <td>yes</td>\n",
       "      <td>southeast</td>\n",
       "      <td>38792.685600</td>\n",
       "      <td>42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1170</th>\n",
       "      <td>18</td>\n",
       "      <td>male</td>\n",
       "      <td>27.360</td>\n",
       "      <td>1</td>\n",
       "      <td>yes</td>\n",
       "      <td>northeast</td>\n",
       "      <td>17178.682400</td>\n",
       "      <td>27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>157</th>\n",
       "      <td>18</td>\n",
       "      <td>male</td>\n",
       "      <td>25.175</td>\n",
       "      <td>0</td>\n",
       "      <td>yes</td>\n",
       "      <td>northeast</td>\n",
       "      <td>15518.180250</td>\n",
       "      <td>25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1282</th>\n",
       "      <td>18</td>\n",
       "      <td>female</td>\n",
       "      <td>21.660</td>\n",
       "      <td>0</td>\n",
       "      <td>yes</td>\n",
       "      <td>northeast</td>\n",
       "      <td>14283.459400</td>\n",
       "      <td>21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1033</th>\n",
       "      <td>18</td>\n",
       "      <td>male</td>\n",
       "      <td>21.565</td>\n",
       "      <td>0</td>\n",
       "      <td>yes</td>\n",
       "      <td>northeast</td>\n",
       "      <td>13747.872350</td>\n",
       "      <td>21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1315</th>\n",
       "      <td>18</td>\n",
       "      <td>male</td>\n",
       "      <td>28.310</td>\n",
       "      <td>1</td>\n",
       "      <td>no</td>\n",
       "      <td>northeast</td>\n",
       "      <td>11272.331390</td>\n",
       "      <td>28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>250</th>\n",
       "      <td>18</td>\n",
       "      <td>male</td>\n",
       "      <td>17.290</td>\n",
       "      <td>2</td>\n",
       "      <td>yes</td>\n",
       "      <td>northeast</td>\n",
       "      <td>12829.455100</td>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>623</th>\n",
       "      <td>18</td>\n",
       "      <td>male</td>\n",
       "      <td>33.535</td>\n",
       "      <td>0</td>\n",
       "      <td>yes</td>\n",
       "      <td>northeast</td>\n",
       "      <td>34617.840650</td>\n",
       "      <td>33</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1150</th>\n",
       "      <td>18</td>\n",
       "      <td>female</td>\n",
       "      <td>30.305</td>\n",
       "      <td>0</td>\n",
       "      <td>no</td>\n",
       "      <td>northeast</td>\n",
       "      <td>2203.735950</td>\n",
       "      <td>30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1296</th>\n",
       "      <td>18</td>\n",
       "      <td>male</td>\n",
       "      <td>26.125</td>\n",
       "      <td>0</td>\n",
       "      <td>no</td>\n",
       "      <td>northeast</td>\n",
       "      <td>1708.925750</td>\n",
       "      <td>26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>427</th>\n",
       "      <td>18</td>\n",
       "      <td>female</td>\n",
       "      <td>29.165</td>\n",
       "      <td>0</td>\n",
       "      <td>no</td>\n",
       "      <td>northeast</td>\n",
       "      <td>7323.734819</td>\n",
       "      <td>29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>295</th>\n",
       "      <td>18</td>\n",
       "      <td>male</td>\n",
       "      <td>22.990</td>\n",
       "      <td>0</td>\n",
       "      <td>no</td>\n",
       "      <td>northeast</td>\n",
       "      <td>1704.568100</td>\n",
       "      <td>22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>529</th>\n",
       "      <td>18</td>\n",
       "      <td>male</td>\n",
       "      <td>25.460</td>\n",
       "      <td>0</td>\n",
       "      <td>no</td>\n",
       "      <td>northeast</td>\n",
       "      <td>1708.001400</td>\n",
       "      <td>25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>121</th>\n",
       "      <td>18</td>\n",
       "      <td>male</td>\n",
       "      <td>23.750</td>\n",
       "      <td>0</td>\n",
       "      <td>no</td>\n",
       "      <td>northeast</td>\n",
       "      <td>1705.624500</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>492</th>\n",
       "      <td>18</td>\n",
       "      <td>female</td>\n",
       "      <td>25.080</td>\n",
       "      <td>0</td>\n",
       "      <td>no</td>\n",
       "      <td>northeast</td>\n",
       "      <td>2196.473200</td>\n",
       "      <td>25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1212</th>\n",
       "      <td>18</td>\n",
       "      <td>male</td>\n",
       "      <td>21.470</td>\n",
       "      <td>0</td>\n",
       "      <td>no</td>\n",
       "      <td>northeast</td>\n",
       "      <td>1702.455300</td>\n",
       "      <td>21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>18</td>\n",
       "      <td>female</td>\n",
       "      <td>26.315</td>\n",
       "      <td>0</td>\n",
       "      <td>no</td>\n",
       "      <td>northeast</td>\n",
       "      <td>2198.189850</td>\n",
       "      <td>26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1163</th>\n",
       "      <td>18</td>\n",
       "      <td>female</td>\n",
       "      <td>28.215</td>\n",
       "      <td>0</td>\n",
       "      <td>no</td>\n",
       "      <td>northeast</td>\n",
       "      <td>2200.830850</td>\n",
       "      <td>28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>648</th>\n",
       "      <td>18</td>\n",
       "      <td>male</td>\n",
       "      <td>28.500</td>\n",
       "      <td>0</td>\n",
       "      <td>no</td>\n",
       "      <td>northeast</td>\n",
       "      <td>1712.227000</td>\n",
       "      <td>28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1334</th>\n",
       "      <td>18</td>\n",
       "      <td>female</td>\n",
       "      <td>31.920</td>\n",
       "      <td>0</td>\n",
       "      <td>no</td>\n",
       "      <td>northeast</td>\n",
       "      <td>2205.980800</td>\n",
       "      <td>31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>102</th>\n",
       "      <td>18</td>\n",
       "      <td>female</td>\n",
       "      <td>30.115</td>\n",
       "      <td>0</td>\n",
       "      <td>no</td>\n",
       "      <td>northeast</td>\n",
       "      <td>21344.846700</td>\n",
       "      <td>30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>18</td>\n",
       "      <td>female</td>\n",
       "      <td>35.625</td>\n",
       "      <td>0</td>\n",
       "      <td>no</td>\n",
       "      <td>northeast</td>\n",
       "      <td>2211.130750</td>\n",
       "      <td>35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>612</th>\n",
       "      <td>18</td>\n",
       "      <td>female</td>\n",
       "      <td>33.155</td>\n",
       "      <td>0</td>\n",
       "      <td>no</td>\n",
       "      <td>northeast</td>\n",
       "      <td>2207.697450</td>\n",
       "      <td>33</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>728</th>\n",
       "      <td>18</td>\n",
       "      <td>female</td>\n",
       "      <td>40.280</td>\n",
       "      <td>0</td>\n",
       "      <td>no</td>\n",
       "      <td>northeast</td>\n",
       "      <td>2217.601200</td>\n",
       "      <td>40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>759</th>\n",
       "      <td>18</td>\n",
       "      <td>male</td>\n",
       "      <td>38.170</td>\n",
       "      <td>0</td>\n",
       "      <td>yes</td>\n",
       "      <td>southeast</td>\n",
       "      <td>36307.798300</td>\n",
       "      <td>38</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1335</th>\n",
       "      <td>18</td>\n",
       "      <td>female</td>\n",
       "      <td>36.850</td>\n",
       "      <td>0</td>\n",
       "      <td>no</td>\n",
       "      <td>southeast</td>\n",
       "      <td>1629.833500</td>\n",
       "      <td>36</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1068</th>\n",
       "      <td>63</td>\n",
       "      <td>male</td>\n",
       "      <td>21.660</td>\n",
       "      <td>1</td>\n",
       "      <td>no</td>\n",
       "      <td>northwest</td>\n",
       "      <td>14349.854400</td>\n",
       "      <td>21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>175</th>\n",
       "      <td>63</td>\n",
       "      <td>female</td>\n",
       "      <td>37.700</td>\n",
       "      <td>0</td>\n",
       "      <td>yes</td>\n",
       "      <td>southwest</td>\n",
       "      <td>48824.450000</td>\n",
       "      <td>37</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1236</th>\n",
       "      <td>63</td>\n",
       "      <td>female</td>\n",
       "      <td>21.660</td>\n",
       "      <td>0</td>\n",
       "      <td>no</td>\n",
       "      <td>northeast</td>\n",
       "      <td>14449.854400</td>\n",
       "      <td>21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>480</th>\n",
       "      <td>63</td>\n",
       "      <td>male</td>\n",
       "      <td>41.325</td>\n",
       "      <td>3</td>\n",
       "      <td>no</td>\n",
       "      <td>northwest</td>\n",
       "      <td>15555.188750</td>\n",
       "      <td>41</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1079</th>\n",
       "      <td>63</td>\n",
       "      <td>male</td>\n",
       "      <td>33.660</td>\n",
       "      <td>3</td>\n",
       "      <td>no</td>\n",
       "      <td>southeast</td>\n",
       "      <td>15161.534400</td>\n",
       "      <td>33</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>63</td>\n",
       "      <td>female</td>\n",
       "      <td>23.085</td>\n",
       "      <td>0</td>\n",
       "      <td>no</td>\n",
       "      <td>northeast</td>\n",
       "      <td>14451.835150</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>251</th>\n",
       "      <td>63</td>\n",
       "      <td>female</td>\n",
       "      <td>32.200</td>\n",
       "      <td>2</td>\n",
       "      <td>yes</td>\n",
       "      <td>southwest</td>\n",
       "      <td>47305.305000</td>\n",
       "      <td>32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1071</th>\n",
       "      <td>63</td>\n",
       "      <td>male</td>\n",
       "      <td>31.445</td>\n",
       "      <td>0</td>\n",
       "      <td>no</td>\n",
       "      <td>northeast</td>\n",
       "      <td>13974.455550</td>\n",
       "      <td>31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>664</th>\n",
       "      <td>64</td>\n",
       "      <td>female</td>\n",
       "      <td>22.990</td>\n",
       "      <td>0</td>\n",
       "      <td>yes</td>\n",
       "      <td>southeast</td>\n",
       "      <td>27037.914100</td>\n",
       "      <td>22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>398</th>\n",
       "      <td>64</td>\n",
       "      <td>male</td>\n",
       "      <td>25.600</td>\n",
       "      <td>2</td>\n",
       "      <td>no</td>\n",
       "      <td>southwest</td>\n",
       "      <td>14988.432000</td>\n",
       "      <td>25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1265</th>\n",
       "      <td>64</td>\n",
       "      <td>male</td>\n",
       "      <td>23.760</td>\n",
       "      <td>0</td>\n",
       "      <td>yes</td>\n",
       "      <td>southeast</td>\n",
       "      <td>26926.514400</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1051</th>\n",
       "      <td>64</td>\n",
       "      <td>male</td>\n",
       "      <td>26.410</td>\n",
       "      <td>0</td>\n",
       "      <td>no</td>\n",
       "      <td>northeast</td>\n",
       "      <td>14394.557900</td>\n",
       "      <td>26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>378</th>\n",
       "      <td>64</td>\n",
       "      <td>female</td>\n",
       "      <td>30.115</td>\n",
       "      <td>3</td>\n",
       "      <td>no</td>\n",
       "      <td>northwest</td>\n",
       "      <td>16455.707850</td>\n",
       "      <td>30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>199</th>\n",
       "      <td>64</td>\n",
       "      <td>female</td>\n",
       "      <td>39.330</td>\n",
       "      <td>0</td>\n",
       "      <td>no</td>\n",
       "      <td>northeast</td>\n",
       "      <td>14901.516700</td>\n",
       "      <td>39</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>94</th>\n",
       "      <td>64</td>\n",
       "      <td>female</td>\n",
       "      <td>31.300</td>\n",
       "      <td>2</td>\n",
       "      <td>yes</td>\n",
       "      <td>southwest</td>\n",
       "      <td>47291.055000</td>\n",
       "      <td>31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>62</th>\n",
       "      <td>64</td>\n",
       "      <td>male</td>\n",
       "      <td>24.700</td>\n",
       "      <td>1</td>\n",
       "      <td>no</td>\n",
       "      <td>northwest</td>\n",
       "      <td>30166.618170</td>\n",
       "      <td>24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>825</th>\n",
       "      <td>64</td>\n",
       "      <td>female</td>\n",
       "      <td>31.825</td>\n",
       "      <td>2</td>\n",
       "      <td>no</td>\n",
       "      <td>northeast</td>\n",
       "      <td>16069.084750</td>\n",
       "      <td>31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>335</th>\n",
       "      <td>64</td>\n",
       "      <td>male</td>\n",
       "      <td>34.500</td>\n",
       "      <td>0</td>\n",
       "      <td>no</td>\n",
       "      <td>southwest</td>\n",
       "      <td>13822.803000</td>\n",
       "      <td>34</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1241</th>\n",
       "      <td>64</td>\n",
       "      <td>male</td>\n",
       "      <td>36.960</td>\n",
       "      <td>2</td>\n",
       "      <td>yes</td>\n",
       "      <td>southeast</td>\n",
       "      <td>49577.662400</td>\n",
       "      <td>36</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>534</th>\n",
       "      <td>64</td>\n",
       "      <td>male</td>\n",
       "      <td>40.480</td>\n",
       "      <td>0</td>\n",
       "      <td>no</td>\n",
       "      <td>southeast</td>\n",
       "      <td>13831.115200</td>\n",
       "      <td>40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>768</th>\n",
       "      <td>64</td>\n",
       "      <td>female</td>\n",
       "      <td>39.700</td>\n",
       "      <td>0</td>\n",
       "      <td>no</td>\n",
       "      <td>southwest</td>\n",
       "      <td>14319.031000</td>\n",
       "      <td>39</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>635</th>\n",
       "      <td>64</td>\n",
       "      <td>male</td>\n",
       "      <td>38.190</td>\n",
       "      <td>0</td>\n",
       "      <td>no</td>\n",
       "      <td>northeast</td>\n",
       "      <td>14410.932100</td>\n",
       "      <td>38</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>890</th>\n",
       "      <td>64</td>\n",
       "      <td>female</td>\n",
       "      <td>26.885</td>\n",
       "      <td>0</td>\n",
       "      <td>yes</td>\n",
       "      <td>northwest</td>\n",
       "      <td>29330.983150</td>\n",
       "      <td>26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>752</th>\n",
       "      <td>64</td>\n",
       "      <td>male</td>\n",
       "      <td>37.905</td>\n",
       "      <td>0</td>\n",
       "      <td>no</td>\n",
       "      <td>northwest</td>\n",
       "      <td>14210.535950</td>\n",
       "      <td>37</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>402</th>\n",
       "      <td>64</td>\n",
       "      <td>female</td>\n",
       "      <td>32.965</td>\n",
       "      <td>0</td>\n",
       "      <td>no</td>\n",
       "      <td>northwest</td>\n",
       "      <td>14692.669350</td>\n",
       "      <td>32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>418</th>\n",
       "      <td>64</td>\n",
       "      <td>male</td>\n",
       "      <td>39.160</td>\n",
       "      <td>1</td>\n",
       "      <td>no</td>\n",
       "      <td>southeast</td>\n",
       "      <td>14418.280400</td>\n",
       "      <td>39</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>603</th>\n",
       "      <td>64</td>\n",
       "      <td>female</td>\n",
       "      <td>39.050</td>\n",
       "      <td>3</td>\n",
       "      <td>no</td>\n",
       "      <td>southeast</td>\n",
       "      <td>16085.127500</td>\n",
       "      <td>39</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>420</th>\n",
       "      <td>64</td>\n",
       "      <td>male</td>\n",
       "      <td>33.880</td>\n",
       "      <td>0</td>\n",
       "      <td>yes</td>\n",
       "      <td>southeast</td>\n",
       "      <td>46889.261200</td>\n",
       "      <td>33</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>328</th>\n",
       "      <td>64</td>\n",
       "      <td>female</td>\n",
       "      <td>33.800</td>\n",
       "      <td>1</td>\n",
       "      <td>yes</td>\n",
       "      <td>southwest</td>\n",
       "      <td>47928.030000</td>\n",
       "      <td>33</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>801</th>\n",
       "      <td>64</td>\n",
       "      <td>female</td>\n",
       "      <td>35.970</td>\n",
       "      <td>0</td>\n",
       "      <td>no</td>\n",
       "      <td>southeast</td>\n",
       "      <td>14313.846300</td>\n",
       "      <td>35</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1338 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      age     sex     bmi  children smoker     region       charges  bmi_int\n",
       "172    18    male  15.960         0     no  northeast   1694.796400       15\n",
       "161    18  female  36.850         0    yes  southeast  36149.483500       36\n",
       "1317   18    male  53.130         0     no  southeast   1163.462700       53\n",
       "940    18    male  23.210         0     no  southeast   1121.873900       23\n",
       "803    18  female  42.240         0    yes  southeast  38792.685600       42\n",
       "1170   18    male  27.360         1    yes  northeast  17178.682400       27\n",
       "157    18    male  25.175         0    yes  northeast  15518.180250       25\n",
       "1282   18  female  21.660         0    yes  northeast  14283.459400       21\n",
       "1033   18    male  21.565         0    yes  northeast  13747.872350       21\n",
       "1315   18    male  28.310         1     no  northeast  11272.331390       28\n",
       "250    18    male  17.290         2    yes  northeast  12829.455100       17\n",
       "623    18    male  33.535         0    yes  northeast  34617.840650       33\n",
       "1150   18  female  30.305         0     no  northeast   2203.735950       30\n",
       "1296   18    male  26.125         0     no  northeast   1708.925750       26\n",
       "427    18  female  29.165         0     no  northeast   7323.734819       29\n",
       "295    18    male  22.990         0     no  northeast   1704.568100       22\n",
       "529    18    male  25.460         0     no  northeast   1708.001400       25\n",
       "121    18    male  23.750         0     no  northeast   1705.624500       23\n",
       "492    18  female  25.080         0     no  northeast   2196.473200       25\n",
       "1212   18    male  21.470         0     no  northeast   1702.455300       21\n",
       "31     18  female  26.315         0     no  northeast   2198.189850       26\n",
       "1163   18  female  28.215         0     no  northeast   2200.830850       28\n",
       "648    18    male  28.500         0     no  northeast   1712.227000       28\n",
       "1334   18  female  31.920         0     no  northeast   2205.980800       31\n",
       "102    18  female  30.115         0     no  northeast  21344.846700       30\n",
       "50     18  female  35.625         0     no  northeast   2211.130750       35\n",
       "612    18  female  33.155         0     no  northeast   2207.697450       33\n",
       "728    18  female  40.280         0     no  northeast   2217.601200       40\n",
       "759    18    male  38.170         0    yes  southeast  36307.798300       38\n",
       "1335   18  female  36.850         0     no  southeast   1629.833500       36\n",
       "...   ...     ...     ...       ...    ...        ...           ...      ...\n",
       "1068   63    male  21.660         1     no  northwest  14349.854400       21\n",
       "175    63  female  37.700         0    yes  southwest  48824.450000       37\n",
       "1236   63  female  21.660         0     no  northeast  14449.854400       21\n",
       "480    63    male  41.325         3     no  northwest  15555.188750       41\n",
       "1079   63    male  33.660         3     no  southeast  15161.534400       33\n",
       "26     63  female  23.085         0     no  northeast  14451.835150       23\n",
       "251    63  female  32.200         2    yes  southwest  47305.305000       32\n",
       "1071   63    male  31.445         0     no  northeast  13974.455550       31\n",
       "664    64  female  22.990         0    yes  southeast  27037.914100       22\n",
       "398    64    male  25.600         2     no  southwest  14988.432000       25\n",
       "1265   64    male  23.760         0    yes  southeast  26926.514400       23\n",
       "1051   64    male  26.410         0     no  northeast  14394.557900       26\n",
       "378    64  female  30.115         3     no  northwest  16455.707850       30\n",
       "199    64  female  39.330         0     no  northeast  14901.516700       39\n",
       "94     64  female  31.300         2    yes  southwest  47291.055000       31\n",
       "62     64    male  24.700         1     no  northwest  30166.618170       24\n",
       "825    64  female  31.825         2     no  northeast  16069.084750       31\n",
       "335    64    male  34.500         0     no  southwest  13822.803000       34\n",
       "1241   64    male  36.960         2    yes  southeast  49577.662400       36\n",
       "534    64    male  40.480         0     no  southeast  13831.115200       40\n",
       "768    64  female  39.700         0     no  southwest  14319.031000       39\n",
       "635    64    male  38.190         0     no  northeast  14410.932100       38\n",
       "890    64  female  26.885         0    yes  northwest  29330.983150       26\n",
       "752    64    male  37.905         0     no  northwest  14210.535950       37\n",
       "402    64  female  32.965         0     no  northwest  14692.669350       32\n",
       "418    64    male  39.160         1     no  southeast  14418.280400       39\n",
       "603    64  female  39.050         3     no  southeast  16085.127500       39\n",
       "420    64    male  33.880         0    yes  southeast  46889.261200       33\n",
       "328    64  female  33.800         1    yes  southwest  47928.030000       33\n",
       "801    64  female  35.970         0     no  southeast  14313.846300       35\n",
       "\n",
       "[1338 rows x 8 columns]"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "v = \"age\"\n",
    "group_df = df.groupby(\"age\").mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "g1 = group_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "group_df = group_df.sort_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "g2 = group_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>sex</th>\n",
       "      <th>bmi</th>\n",
       "      <th>children</th>\n",
       "      <th>smoker</th>\n",
       "      <th>region</th>\n",
       "      <th>charges</th>\n",
       "      <th>bmi_int</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>age</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>0.521739</td>\n",
       "      <td>31.326159</td>\n",
       "      <td>0.449275</td>\n",
       "      <td>0.173913</td>\n",
       "      <td>1.072464</td>\n",
       "      <td>7086.217556</td>\n",
       "      <td>30.942029</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>0.514706</td>\n",
       "      <td>28.596912</td>\n",
       "      <td>0.426471</td>\n",
       "      <td>0.264706</td>\n",
       "      <td>1.955882</td>\n",
       "      <td>9747.909335</td>\n",
       "      <td>28.044118</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>0.517241</td>\n",
       "      <td>30.632759</td>\n",
       "      <td>0.862069</td>\n",
       "      <td>0.310345</td>\n",
       "      <td>1.620690</td>\n",
       "      <td>10159.697736</td>\n",
       "      <td>30.172414</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>0.535714</td>\n",
       "      <td>28.185714</td>\n",
       "      <td>0.785714</td>\n",
       "      <td>0.071429</td>\n",
       "      <td>1.500000</td>\n",
       "      <td>4730.464330</td>\n",
       "      <td>27.642857</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>0.535714</td>\n",
       "      <td>31.087679</td>\n",
       "      <td>0.714286</td>\n",
       "      <td>0.214286</td>\n",
       "      <td>1.464286</td>\n",
       "      <td>10012.932802</td>\n",
       "      <td>30.642857</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>0.500000</td>\n",
       "      <td>31.454464</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.250000</td>\n",
       "      <td>1.500000</td>\n",
       "      <td>12419.820040</td>\n",
       "      <td>30.964286</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>0.500000</td>\n",
       "      <td>29.142679</td>\n",
       "      <td>0.464286</td>\n",
       "      <td>0.214286</td>\n",
       "      <td>1.500000</td>\n",
       "      <td>10648.015962</td>\n",
       "      <td>28.642857</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>0.535714</td>\n",
       "      <td>29.693929</td>\n",
       "      <td>1.285714</td>\n",
       "      <td>0.178571</td>\n",
       "      <td>1.500000</td>\n",
       "      <td>9838.365311</td>\n",
       "      <td>29.142857</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>0.535714</td>\n",
       "      <td>29.428929</td>\n",
       "      <td>1.071429</td>\n",
       "      <td>0.107143</td>\n",
       "      <td>1.500000</td>\n",
       "      <td>6133.825309</td>\n",
       "      <td>28.928571</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>0.500000</td>\n",
       "      <td>29.333571</td>\n",
       "      <td>0.964286</td>\n",
       "      <td>0.321429</td>\n",
       "      <td>1.500000</td>\n",
       "      <td>12184.701721</td>\n",
       "      <td>28.928571</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>0.500000</td>\n",
       "      <td>29.482143</td>\n",
       "      <td>1.285714</td>\n",
       "      <td>0.107143</td>\n",
       "      <td>1.535714</td>\n",
       "      <td>9069.187564</td>\n",
       "      <td>28.964286</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>0.518519</td>\n",
       "      <td>29.383148</td>\n",
       "      <td>1.259259</td>\n",
       "      <td>0.222222</td>\n",
       "      <td>1.444444</td>\n",
       "      <td>10430.158727</td>\n",
       "      <td>28.814815</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>0.518519</td>\n",
       "      <td>30.557593</td>\n",
       "      <td>1.555556</td>\n",
       "      <td>0.333333</td>\n",
       "      <td>1.592593</td>\n",
       "      <td>12719.110358</td>\n",
       "      <td>30.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>0.518519</td>\n",
       "      <td>29.918333</td>\n",
       "      <td>1.407407</td>\n",
       "      <td>0.185185</td>\n",
       "      <td>1.444444</td>\n",
       "      <td>10196.980573</td>\n",
       "      <td>29.370370</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>0.500000</td>\n",
       "      <td>31.597692</td>\n",
       "      <td>1.269231</td>\n",
       "      <td>0.192308</td>\n",
       "      <td>1.576923</td>\n",
       "      <td>9220.300291</td>\n",
       "      <td>31.076923</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          sex        bmi  children    smoker    region       charges  \\\n",
       "age                                                                    \n",
       "18   0.521739  31.326159  0.449275  0.173913  1.072464   7086.217556   \n",
       "19   0.514706  28.596912  0.426471  0.264706  1.955882   9747.909335   \n",
       "20   0.517241  30.632759  0.862069  0.310345  1.620690  10159.697736   \n",
       "21   0.535714  28.185714  0.785714  0.071429  1.500000   4730.464330   \n",
       "22   0.535714  31.087679  0.714286  0.214286  1.464286  10012.932802   \n",
       "23   0.500000  31.454464  1.000000  0.250000  1.500000  12419.820040   \n",
       "24   0.500000  29.142679  0.464286  0.214286  1.500000  10648.015962   \n",
       "25   0.535714  29.693929  1.285714  0.178571  1.500000   9838.365311   \n",
       "26   0.535714  29.428929  1.071429  0.107143  1.500000   6133.825309   \n",
       "27   0.500000  29.333571  0.964286  0.321429  1.500000  12184.701721   \n",
       "28   0.500000  29.482143  1.285714  0.107143  1.535714   9069.187564   \n",
       "29   0.518519  29.383148  1.259259  0.222222  1.444444  10430.158727   \n",
       "30   0.518519  30.557593  1.555556  0.333333  1.592593  12719.110358   \n",
       "31   0.518519  29.918333  1.407407  0.185185  1.444444  10196.980573   \n",
       "32   0.500000  31.597692  1.269231  0.192308  1.576923   9220.300291   \n",
       "\n",
       "       bmi_int  \n",
       "age             \n",
       "18   30.942029  \n",
       "19   28.044118  \n",
       "20   30.172414  \n",
       "21   27.642857  \n",
       "22   30.642857  \n",
       "23   30.964286  \n",
       "24   28.642857  \n",
       "25   29.142857  \n",
       "26   28.928571  \n",
       "27   28.928571  \n",
       "28   28.964286  \n",
       "29   28.814815  \n",
       "30   30.000000  \n",
       "31   29.370370  \n",
       "32   31.076923  "
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "g1.head(15)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>sex</th>\n",
       "      <th>bmi</th>\n",
       "      <th>children</th>\n",
       "      <th>smoker</th>\n",
       "      <th>region</th>\n",
       "      <th>charges</th>\n",
       "      <th>bmi_int</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>age</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>0.521739</td>\n",
       "      <td>31.326159</td>\n",
       "      <td>0.449275</td>\n",
       "      <td>0.173913</td>\n",
       "      <td>1.072464</td>\n",
       "      <td>7086.217556</td>\n",
       "      <td>30.942029</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>0.514706</td>\n",
       "      <td>28.596912</td>\n",
       "      <td>0.426471</td>\n",
       "      <td>0.264706</td>\n",
       "      <td>1.955882</td>\n",
       "      <td>9747.909335</td>\n",
       "      <td>28.044118</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>0.517241</td>\n",
       "      <td>30.632759</td>\n",
       "      <td>0.862069</td>\n",
       "      <td>0.310345</td>\n",
       "      <td>1.620690</td>\n",
       "      <td>10159.697736</td>\n",
       "      <td>30.172414</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>0.535714</td>\n",
       "      <td>28.185714</td>\n",
       "      <td>0.785714</td>\n",
       "      <td>0.071429</td>\n",
       "      <td>1.500000</td>\n",
       "      <td>4730.464330</td>\n",
       "      <td>27.642857</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>0.535714</td>\n",
       "      <td>31.087679</td>\n",
       "      <td>0.714286</td>\n",
       "      <td>0.214286</td>\n",
       "      <td>1.464286</td>\n",
       "      <td>10012.932802</td>\n",
       "      <td>30.642857</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>0.500000</td>\n",
       "      <td>31.454464</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.250000</td>\n",
       "      <td>1.500000</td>\n",
       "      <td>12419.820040</td>\n",
       "      <td>30.964286</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>0.500000</td>\n",
       "      <td>29.142679</td>\n",
       "      <td>0.464286</td>\n",
       "      <td>0.214286</td>\n",
       "      <td>1.500000</td>\n",
       "      <td>10648.015962</td>\n",
       "      <td>28.642857</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>0.535714</td>\n",
       "      <td>29.693929</td>\n",
       "      <td>1.285714</td>\n",
       "      <td>0.178571</td>\n",
       "      <td>1.500000</td>\n",
       "      <td>9838.365311</td>\n",
       "      <td>29.142857</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>0.535714</td>\n",
       "      <td>29.428929</td>\n",
       "      <td>1.071429</td>\n",
       "      <td>0.107143</td>\n",
       "      <td>1.500000</td>\n",
       "      <td>6133.825309</td>\n",
       "      <td>28.928571</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>0.500000</td>\n",
       "      <td>29.333571</td>\n",
       "      <td>0.964286</td>\n",
       "      <td>0.321429</td>\n",
       "      <td>1.500000</td>\n",
       "      <td>12184.701721</td>\n",
       "      <td>28.928571</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>0.500000</td>\n",
       "      <td>29.482143</td>\n",
       "      <td>1.285714</td>\n",
       "      <td>0.107143</td>\n",
       "      <td>1.535714</td>\n",
       "      <td>9069.187564</td>\n",
       "      <td>28.964286</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>0.518519</td>\n",
       "      <td>29.383148</td>\n",
       "      <td>1.259259</td>\n",
       "      <td>0.222222</td>\n",
       "      <td>1.444444</td>\n",
       "      <td>10430.158727</td>\n",
       "      <td>28.814815</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>0.518519</td>\n",
       "      <td>30.557593</td>\n",
       "      <td>1.555556</td>\n",
       "      <td>0.333333</td>\n",
       "      <td>1.592593</td>\n",
       "      <td>12719.110358</td>\n",
       "      <td>30.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>0.518519</td>\n",
       "      <td>29.918333</td>\n",
       "      <td>1.407407</td>\n",
       "      <td>0.185185</td>\n",
       "      <td>1.444444</td>\n",
       "      <td>10196.980573</td>\n",
       "      <td>29.370370</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>0.500000</td>\n",
       "      <td>31.597692</td>\n",
       "      <td>1.269231</td>\n",
       "      <td>0.192308</td>\n",
       "      <td>1.576923</td>\n",
       "      <td>9220.300291</td>\n",
       "      <td>31.076923</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          sex        bmi  children    smoker    region       charges  \\\n",
       "age                                                                    \n",
       "18   0.521739  31.326159  0.449275  0.173913  1.072464   7086.217556   \n",
       "19   0.514706  28.596912  0.426471  0.264706  1.955882   9747.909335   \n",
       "20   0.517241  30.632759  0.862069  0.310345  1.620690  10159.697736   \n",
       "21   0.535714  28.185714  0.785714  0.071429  1.500000   4730.464330   \n",
       "22   0.535714  31.087679  0.714286  0.214286  1.464286  10012.932802   \n",
       "23   0.500000  31.454464  1.000000  0.250000  1.500000  12419.820040   \n",
       "24   0.500000  29.142679  0.464286  0.214286  1.500000  10648.015962   \n",
       "25   0.535714  29.693929  1.285714  0.178571  1.500000   9838.365311   \n",
       "26   0.535714  29.428929  1.071429  0.107143  1.500000   6133.825309   \n",
       "27   0.500000  29.333571  0.964286  0.321429  1.500000  12184.701721   \n",
       "28   0.500000  29.482143  1.285714  0.107143  1.535714   9069.187564   \n",
       "29   0.518519  29.383148  1.259259  0.222222  1.444444  10430.158727   \n",
       "30   0.518519  30.557593  1.555556  0.333333  1.592593  12719.110358   \n",
       "31   0.518519  29.918333  1.407407  0.185185  1.444444  10196.980573   \n",
       "32   0.500000  31.597692  1.269231  0.192308  1.576923   9220.300291   \n",
       "\n",
       "       bmi_int  \n",
       "age             \n",
       "18   30.942029  \n",
       "19   28.044118  \n",
       "20   30.172414  \n",
       "21   27.642857  \n",
       "22   30.642857  \n",
       "23   30.964286  \n",
       "24   28.642857  \n",
       "25   29.142857  \n",
       "26   28.928571  \n",
       "27   28.928571  \n",
       "28   28.964286  \n",
       "29   28.814815  \n",
       "30   30.000000  \n",
       "31   29.370370  \n",
       "32   31.076923  "
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "g2.head(15)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "平均医疗开销分析：\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYcAAAEGCAYAAACO8lkDAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nQZJUMRwkSRXDQZJUMRwkSRXDQZJU+f9vXFo8dNpv9wAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYcAAAEGCAYAAACO8lkDAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nSVKL4SBJajEcJEkt/x8Zek9nWUYKFwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYcAAAEGCAYAAACO8lkDAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMi4zLCBo\ndHRwOi8vbWF0cGxvdGxpYi5vcmcvIxREBQAAF7FJREFUeJzt3X2QXXWd5/H3Nw8Q5TmkZZk0krhE\nYggQoBMyxhKLTCXhQRI0uFAUBGTJHwZlZGrlabZwBXa1hloURBzKRIPFgIjjkHKibASEVSZAggwY\nAqRFMB15aJIIRha15bt/3F+Ya043HfpecruT96vqVp/zPb9z7vfcqvQn5+GejsxEkqR6w1rdgCRp\n8DEcJEkVhoMkqcJwkCRVGA6SpArDQZJUYThIkioMB0lSheEgSaoY0eoGBmrMmDE5bty4VrchSUPK\n6tWrX87Mtv7GDdlwGDduHKtWrWp1G5I0pETEc9szztNKkqQKw0GSVGE4SJIqhuw1B0m7nj/96U90\ndXXx+uuvt7qVQW/UqFG0t7czcuTIAa1vOEgaMrq6uthrr70YN24cEdHqdgatzGTjxo10dXUxfvz4\nAW3D00qShozXX3+d/fff32DoR0Sw//77N3SEZThIGlIMhu3T6OdkOEiSKrzmIA0B4y7511a3sF2e\n/eJJO/T9mv25DKT/c845h5NPPpn58+c3tZdW88hBklokM3njjTda3UavDAdJehtuvvlmjjjiCI48\n8kjOOussAO6//34++MEP8r73vY877rgDgC1btjBz5kyOPvpoDj/8cO68804Ann32WQ499FDOPvts\nJk+ezPr161m8eDHvf//7mTZtGueffz4XXHABAN3d3Xz84x9n6tSpTJ06lZ/97GcA3HfffUyZMoUp\nU6Zw1FFH8bvf/a7p++lpJUnaTmvWrOGqq67igQceYMyYMWzatImLLrqI559/np/+9Kc8+eSTnHLK\nKcyfP59Ro0bx/e9/n7333puXX36Z6dOnc8oppwCwbt06li5dyvTp0/nNb37DlVdeySOPPMJee+3F\n8ccfz5FHHgnAhRdeyGc/+1k+9KEP8etf/5rZs2ezdu1arrnmGm644QZmzJjBli1bGDVqVNP31XCQ\npO10zz33cNpppzFmzBgARo8eDcC8efMYNmwYkyZN4sUXXwRqp4wuu+wy7r//foYNG8aGDRveXHbw\nwQczffp0AB566CGOO+64N7d12mmn8fTTTwPw4x//mCeeeOLN93/11VfZsmULM2bM4KKLLuLMM8/k\nYx/7GO3t7U3fV8NBkhq0++67vzmdmQDccsstdHd3s3r1akaOHMm4cePe/N7BHnvssV3bfeONN1i5\ncmXlyOCSSy7hpJNOYvny5cyYMYO77rqLiRMnNmlvarzmIEnb6fjjj+e73/0uGzduBGDTpk19jn3l\nlVd4z3vew8iRI7n33nt57rnen5Q9depU7rvvPjZv3kxPTw/f+9733lw2a9Ysrr/++jfnH330UQB+\n+ctfcvjhh3PxxRczdepUnnzyyWbs3l/o98ghIpYAJwMvZebkbZb9HXAN0JaZL0ftWxdfAU4EXgPO\nycxHytgFwN+XVa/KzKWlfgzwLeBdwHLgwtwavZL0Fnb0rbOHHXYYl19+OccddxzDhw/nqKOO6nPs\nmWeeyUc/+lEOP/xwOjo6+vyf/dixY7nsssuYNm0ao0ePZuLEieyzzz4AXHfddSxatIgjjjiCnp4e\nPvzhD/P1r3+dL3/5y9x7770MGzaMww47jBNOOKHp+xr9/R6OiA8DW4Cb68MhIg4CvgFMBI4p4XAi\n8Glq4XAs8JXMPDYiRgOrgA4ggdVlnc0R8RDwGeBBauFwXWb+sL/GOzo60j/2o12F33OoWbt2LR/4\nwAfe0fdohS1btrDnnnvS09PDqaeeyic/+UlOPfXUhrfb2+cVEaszs6O/dfs9rZSZ9wO9HTtdC3yO\n2i/7reZSC5HMzJXAvhFxIDAbWJGZmzJzM7ACmFOW7Z2ZK8vRws3AvP56kqSdyec//3mmTJnC5MmT\nGT9+PPPmtf7X4IAuSEfEXGBDZv77Ns/vGAusr5vvKrW3qnf1UpekXcY111zT6hYq3nY4RMS7gcuA\nWc1vp9/3XggsBHjve9+7o99e0iCQmT58bzs0eul2IHcr/WdgPPDvEfEs0A48EhH/CdgAHFQ3tr3U\n3qre3ku9V5l5U2Z2ZGZHW1vbAFqXNJSNGjWKjRs3NvyLb2e39e85NPLluLd95JCZjwPv2TpfAqKj\nXJBeBlwQEbdRuyD9SmY+HxF3Af8zIvYrq80CLs3MTRHxakRMp3ZB+mzgeiSpF+3t7XR1ddHd3d3q\nVga9rX8JbqC251bWW4GPAGMiogu4IjMX9zF8ObU7lTqp3cp6LkAJgSuBh8u4L2Tm1ovcn+I/bmX9\nYXlJUsXIkSMH/JfN9Pb0Gw6ZeUY/y8fVTSewqI9xS4AlvdRXAZOra0iSWsVvSEuSKgwHSVKF4SBJ\nqvCprHWGwiMKdvSzZCTtmjxykCRVGA6SpArDQZJUYThIkioMB0lSheEgSaowHCRJFYaDJKnCcJAk\nVRgOkqQKw0GSVGE4SJIqDAdJUoVPZdU7Yig84RZ8yq3UF8NB0i7H/7z0r9/TShGxJCJeiohf1NX+\nISKejIjHIuL7EbFv3bJLI6IzIp6KiNl19Tml1hkRl9TVx0fEg6X+nYjYrZk7KEl6+7bnmsO3gDnb\n1FYAkzPzCOBp4FKAiJgEnA4cVtb5WkQMj4jhwA3ACcAk4IwyFuBLwLWZeQiwGTivoT2SJDWs33DI\nzPuBTdvU/k9m9pTZlUB7mZ4L3JaZf8jMXwGdwLTy6szMZzLzj8BtwNyICOB44I6y/lJgXoP7JElq\nUDPuVvok8MMyPRZYX7esq9T6qu8P/LYuaLbWJUkt1FA4RMTlQA9wS3Pa6ff9FkbEqohY1d3dvSPe\nUpJ2SQMOh4g4BzgZODMzs5Q3AAfVDWsvtb7qG4F9I2LENvVeZeZNmdmRmR1tbW0DbV2S1I8BhUNE\nzAE+B5ySma/VLVoGnB4Ru0fEeGAC8BDwMDCh3Jm0G7WL1stKqNwLzC/rLwDuHNiuSJKaZXtuZb0V\n+Dfg0IjoiojzgK8CewErIuLRiPg6QGauAW4HngB+BCzKzD+XawoXAHcBa4Hby1iAi4GLIqKT2jWI\nxU3dQ0nS29bvl+Ay84xeyn3+As/Mq4Gre6kvB5b3Un+G2t1MkqRBwmcrSZIqDAdJUoXhIEmqMBwk\nSRWGgySpwnCQJFUYDpKkCsNBklRhOEiSKgwHSVKF4SBJqjAcJEkVhoMkqcJwkCRVGA6SpArDQZJU\nYThIkioMB0lSheEgSaowHCRJFf2GQ0QsiYiXIuIXdbXREbEiItaVn/uVekTEdRHRGRGPRcTRdess\nKOPXRcSCuvoxEfF4Wee6iIhm76Qk6e3ZniOHbwFztqldAtydmROAu8s8wAnAhPJaCNwItTABrgCO\nBaYBV2wNlDLm/Lr1tn0vSdIO1m84ZOb9wKZtynOBpWV6KTCvrn5z1qwE9o2IA4HZwIrM3JSZm4EV\nwJyybO/MXJmZCdxcty1JUosM9JrDAZn5fJl+ATigTI8F1teN6yq1t6p39VLvVUQsjIhVEbGqu7t7\ngK1LkvrT8AXp8j/+bEIv2/NeN2VmR2Z2tLW17Yi3lKRd0kDD4cVySojy86VS3wAcVDeuvdTeqt7e\nS12S1EIDDYdlwNY7jhYAd9bVzy53LU0HXimnn+4CZkXEfuVC9CzgrrLs1YiYXu5SOrtuW5KkFhnR\n34CIuBX4CDAmIrqo3XX0ReD2iDgPeA74RBm+HDgR6AReA84FyMxNEXEl8HAZ94XM3HqR+1PU7oh6\nF/DD8pIktVC/4ZCZZ/SxaGYvYxNY1Md2lgBLeqmvAib314ckacfxG9KSpArDQZJUYThIkioMB0lS\nheEgSaowHCRJFYaDJKnCcJAkVRgOkqQKw0GSVGE4SJIqDAdJUoXhIEmqMBwkSRWGgySpwnCQJFUY\nDpKkCsNBklRhOEiSKhoKh4j4bESsiYhfRMStETEqIsZHxIMR0RkR34mI3crY3ct8Z1k+rm47l5b6\nUxExu7FdkiQ1asDhEBFjgc8AHZk5GRgOnA58Cbg2Mw8BNgPnlVXOAzaX+rVlHBExqax3GDAH+FpE\nDB9oX5KkxjV6WmkE8K6IGAG8G3geOB64oyxfCswr03PLPGX5zIiIUr8tM/+Qmb8COoFpDfYlSWrA\ngMMhMzcA1wC/phYKrwCrgd9mZk8Z1gWMLdNjgfVl3Z4yfv/6ei/r/IWIWBgRqyJiVXd390BblyT1\no5HTSvtR+1//eOCvgD2onRZ6x2TmTZnZkZkdbW1t7+RbSdIurZHTSn8D/CozuzPzT8A/AzOAfctp\nJoB2YEOZ3gAcBFCW7wNsrK/3so4kqQUaCYdfA9Mj4t3l2sFM4AngXmB+GbMAuLNMLyvzlOX3ZGaW\n+unlbqbxwATgoQb6kiQ1aET/Q3qXmQ9GxB3AI0AP8HPgJuBfgdsi4qpSW1xWWQx8OyI6gU3U7lAi\nM9dExO3UgqUHWJSZfx5oX5Kkxg04HAAy8wrgim3Kz9DL3UaZ+TpwWh/buRq4upFeJEnN4zekJUkV\nhoMkqcJwkCRVGA6SpArDQZJUYThIkioMB0lSheEgSaowHCRJFYaDJKnCcJAkVRgOkqQKw0GSVGE4\nSJIqDAdJUoXhIEmqMBwkSRWGgySpwnCQJFU0FA4RsW9E3BERT0bE2oj464gYHRErImJd+blfGRsR\ncV1EdEbEYxFxdN12FpTx6yJiQaM7JUlqTKNHDl8BfpSZE4EjgbXAJcDdmTkBuLvMA5wATCivhcCN\nABExGrgCOBaYBlyxNVAkSa0x4HCIiH2ADwOLATLzj5n5W2AusLQMWwrMK9NzgZuzZiWwb0QcCMwG\nVmTmpszcDKwA5gy0L0lS4xo5chgPdAPfjIifR8Q3ImIP4IDMfL6MeQE4oEyPBdbXrd9Van3VKyJi\nYUSsiohV3d3dDbQuSXorjYTDCOBo4MbMPAr4Pf9xCgmAzEwgG3iPv5CZN2VmR2Z2tLW1NWuzkqRt\nNBIOXUBXZj5Y5u+gFhYvltNFlJ8vleUbgIPq1m8vtb7qkqQWGXA4ZOYLwPqIOLSUZgJPAMuArXcc\nLQDuLNPLgLPLXUvTgVfK6ae7gFkRsV+5ED2r1CRJLTKiwfU/DdwSEbsBzwDnUguc2yPiPOA54BNl\n7HLgRKATeK2MJTM3RcSVwMNl3Bcyc1ODfUmSGtBQOGTmo0BHL4tm9jI2gUV9bGcJsKSRXiRJzeM3\npCVJFYaDJKnCcJAkVRgOkqQKw0GSVGE4SJIqDAdJUoXhIEmqMBwkSRWGgySpwnCQJFUYDpKkCsNB\nklRhOEiSKgwHSVKF4SBJqjAcJEkVhoMkqcJwkCRVNBwOETE8In4eET8o8+Mj4sGI6IyI70TEbqW+\ne5nvLMvH1W3j0lJ/KiJmN9qTJKkxzThyuBBYWzf/JeDazDwE2AycV+rnAZtL/doyjoiYBJwOHAbM\nAb4WEcOb0JckaYAaCoeIaAdOAr5R5gM4HrijDFkKzCvTc8s8ZfnMMn4ucFtm/iEzfwV0AtMa6UuS\n1JhGjxy+DHwOeKPM7w/8NjN7ynwXMLZMjwXWA5Tlr5Txb9Z7WecvRMTCiFgVEau6u7sbbF2S1JcB\nh0NEnAy8lJmrm9jPW8rMmzKzIzM72tradtTbStIuZ0QD684ATomIE4FRwN7AV4B9I2JEOTpoBzaU\n8RuAg4CuiBgB7ANsrKtvVb+OJKkFBnzkkJmXZmZ7Zo6jdkH5nsw8E7gXmF+GLQDuLNPLyjxl+T2Z\nmaV+ermbaTwwAXhooH1JkhrXyJFDXy4GbouIq4CfA4tLfTHw7YjoBDZRCxQyc01E3A48AfQAizLz\nz+9AX5Kk7dSUcMjMnwA/KdPP0MvdRpn5OnBaH+tfDVzdjF4kSY3zG9KSpArDQZJUYThIkioMB0lS\nheEgSaowHCRJFYaDJKnCcJAkVRgOkqQKw0GSVGE4SJIqDAdJUoXhIEmqMBwkSRWGgySpwnCQJFUY\nDpKkCsNBklRhOEiSKgYcDhFxUETcGxFPRMSaiLiw1EdHxIqIWFd+7lfqERHXRURnRDwWEUfXbWtB\nGb8uIhY0vluSpEY0cuTQA/xdZk4CpgOLImIScAlwd2ZOAO4u8wAnABPKayFwI9TCBLgCOBaYBlyx\nNVAkSa0x4HDIzOcz85Ey/TtgLTAWmAssLcOWAvPK9Fzg5qxZCewbEQcCs4EVmbkpMzcDK4A5A+1L\nktS4plxziIhxwFHAg8ABmfl8WfQCcECZHgusr1utq9T6qvf2PgsjYlVErOru7m5G65KkXjQcDhGx\nJ/A94G8z89X6ZZmZQDb6HnXbuykzOzKzo62trVmblSRto6FwiIiR1ILhlsz851J+sZwuovx8qdQ3\nAAfVrd5ean3VJUkt0sjdSgEsBtZm5v+uW7QM2HrH0QLgzrr62eWupenAK+X0013ArIjYr1yInlVq\nkqQWGdHAujOAs4DHI+LRUrsM+CJwe0ScBzwHfKIsWw6cCHQCrwHnAmTmpoi4Eni4jPtCZm5qoC9J\nUoMGHA6Z+VMg+lg8s5fxCSzqY1tLgCUD7UWS1Fx+Q1qSVGE4SJIqDAdJUoXhIEmqMBwkSRWGgySp\nwnCQJFUYDpKkCsNBklRhOEiSKgwHSVKF4SBJqjAcJEkVhoMkqcJwkCRVGA6SpArDQZJUYThIkioM\nB0lSxaAJh4iYExFPRURnRFzS6n4kaVc2KMIhIoYDNwAnAJOAMyJiUmu7kqRd16AIB2Aa0JmZz2Tm\nH4HbgLkt7kmSdlmRma3ugYiYD8zJzP9a5s8Cjs3MC7YZtxBYWGYPBZ7aoY0OzBjg5VY3sZPws2wu\nP8/mGiqf58GZ2dbfoBE7opNmycybgJta3cfbERGrMrOj1X3sDPwsm8vPs7l2ts9zsJxW2gAcVDff\nXmqSpBYYLOHwMDAhIsZHxG7A6cCyFvckSbusQXFaKTN7IuIC4C5gOLAkM9e0uK1mGVKnwQY5P8vm\n8vNsrp3q8xwUF6QlSYPLYDmtJEkaRAwHSVKF4SBJqhgUF6R3FhExkdo3u8eW0gZgWWaubV1Xkpot\nIqYBmZkPl0f9zAGezMzlLW6taTxyaJKIuJjaYz8CeKi8ArjVBwlqMIiIiRExMyL23KY+p1U9DUUR\ncQVwHXBjRPwv4KvAHsAlEXF5S5trIu9WapKIeBo4LDP/tE19N2BNZk5oTWc7n4g4NzO/2eo+hpKI\n+AywCFgLTAEuzMw7y7JHMvPoVvY3lETE49Q+w92BF4D2zHw1It4FPJiZR7S0wSbxyKF53gD+qpf6\ngWWZmud/tLqBIeh84JjMnAd8BPjvEXFhWRYt62po6snMP2fma8AvM/NVgMz8f+xE/9a95tA8fwvc\nHRHrgPWl9l7gEOCCPtdSryLisb4WAQfsyF52EsMycwtAZj4bER8B7oiIgzEc3q4/RsS7Szgcs7UY\nEfuwE4WDp5WaKCKGUXv8eP0F6Ycz88+t62poiogXgdnA5m0XAQ9kZm9HaepDRNwDXJSZj9bVRgBL\ngDMzc3jLmhtiImL3zPxDL/UxwIGZ+XgL2mo6jxyaKDPfAFa2uo+dxA+APet/mW0VET/Z8e0MeWcD\nPfWFzOwBzo6If2xNS0NTb8FQ6i8zNB7ZvV08cpAkVXhBWpJUYThIkioMB+kdEBGn+OVHDWVec5D6\nERFB7d/KTnObotQfjxykXkTEuIh4KiJuBn4BnBUR/xYRj0TEd7c+giIiToyIJyNidURcFxE/KPVz\nIuKrddu6JyIei4i7I+K9pf6tss4DEfFMRMxv1f5K2zIcpL5NAL4GHAecB/xNeczEKuCiiBgF/CNw\nQmYeA7T1sZ3rgaXlsQq3UHsuz1YHAh8CTga++I7shTQAhoPUt+cycyUwHZgE/CwiHgUWAAcDE4Fn\nMvNXZfytfWznr4F/KtPfphYGW/1LZr6RmU/gN781iPglOKlvvy8/A1iRmWfUL4yIKU14j/ovVPkY\nCw0aHjlI/VsJzIiIQwAiYo+IeD/wFPC+iBhXxv2XPtZ/ADi9TJ8J/N93rlWpOTxykPqRmd0RcQ61\nv82xeyn/fWY+HRGfAn4UEb8HHu5jE58GvhkR/w3oBs59x5uWGuStrFIDImLPzNxSbne9AViXmde2\nui+pUZ5WkhpzfrlIvQbYh9rdS9KQ55GDJKnCIwdJUoXhIEmqMBwkSRWGgySpwnCQJFX8f5fFCD+l\noi7QAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYcAAAENCAYAAADkNanAAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nk4MkqcLkIEmqMDlIkir+P6T9Uy9rxaOXAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYcAAAENCAYAAADkNanAAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\ncpAklfwXG+X4LcTNJbAAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYcAAAEGCAYAAACO8lkDAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#平均医疗开销分析 张子豪\n",
    "print('平均医疗开销分析：')\n",
    "for v in variables:\n",
    "    group_df = df.groupby(v).mean()\n",
    "    group_df.plot(y = ['charges'],kind = 'bar')\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {
    "_cell_guid": "98eb1d06-25c7-4fcd-a237-6b8430d006e5",
    "_uuid": "6809020e5490a674d3c1e7ed88ca1d56aec2413c",
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "平均医疗开销分析：\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYcAAAEGCAYAAACO8lkDAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nQZJUMRwkSRXDQZJUMRwkSRXDQZJU+f9vXFo8dNpv9wAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYcAAAEGCAYAAACO8lkDAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nSVKL4SBJajEcJEkt/x8Zek9nWUYKFwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYcAAAEGCAYAAACO8lkDAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\noi7QAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYcAAAENCAYAAADkNanAAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nk4MkqcLkIEmqMDlIkir+P6T9Uy9rxaOXAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYcAAAENCAYAAADkNanAAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMi4zLCBo\ndHRwOi8vbWF0cGxvdGxpYi5vcmcvIxREBQAAHGlJREFUeJzt3XuYHVWZqPH3y0Wics1FxAToqAEM\nCQTshGgYwTBCAIWgwcHhcFGEmSMoI54ZI3oOyMXBGUYUB1GORILiAQQdOBAnByXCgBNCCBgM4RIi\nl0SEkEQgR0EDa/6o1WRnV192d3Z67+5+f89TT1et+vbaq1b3rq9qVe3qSCkhSVKlQY1ugCSp+Zgc\nJEklJgdJUonJQZJUYnKQJJWYHCRJJSYHSVKJyUGSVGJykCSVDGl0A3pq5MiRqaWlpdHNkKQ+4777\n7ns+pTSqltg+mxxaWlpYvHhxo5shSX1GRDxZa6zDSpKkEpODJKnE5CBJKumz1xza8+c//5lVq1bx\n8ssvN7opTW3YsGGMGTOGoUOHNropkppUv0oOq1atYrvttqOlpYWIaHRzmlJKibVr17Jq1SrGjh3b\n6OZIalL9aljp5ZdfZsSIESaGTkQEI0aM8OxKUqf6VXIATAw1sI8kdaXfJQdJ0pbrV9ccqrXMvrWu\n9T1x0ZHdfs3JJ5/MBz/4QWbNmlXXtkgamKr3az3ZL9XCM4cmllLitddea3QzJA1AJoc6u/rqq9ln\nn33Yd999OeGEEwC48847ee9738vb3/52brjhBgA2bNjAIYccwv7778/EiRO56aabAHjiiSfYc889\nOfHEE5kwYQJPP/00V155JXvssQdTpkzh1FNP5YwzzgBgzZo1fOQjH2Hy5MlMnjyZu+++G4A77riD\nSZMmMWnSJPbbbz9eeumlBvSEpL6sXw8r9bZly5ZxwQUX8Mtf/pKRI0eybt06zjrrLJ555hnuuusu\nHn74YY466ihmzZrFsGHD+MlPfsL222/P888/z9SpUznqqKMAeOyxx5g7dy5Tp07lt7/9Leeffz5L\nlixhu+22Y/r06ey7774AnHnmmXz2s5/lwAMP5KmnnuKwww5j+fLlXHzxxVx22WVMmzaNDRs2MGzY\nsEZ2i6Q+yORQR7fffjvHHnssI0eOBGD48OEAzJw5k0GDBjF+/HieffZZoBgyOvvss7nzzjsZNGgQ\nq1evfn3d7rvvztSpUwFYtGgRBx100Ot1HXvssTz66KMA/OxnP+Ohhx56/f1ffPFFNmzYwLRp0zjr\nrLM4/vjj+fCHP8yYMWN6pwMk9Rsmh16wzTbbvD6fUgLgmmuuYc2aNdx3330MHTqUlpaW17978OY3\nv7mmel977TUWLlxYOjOYPXs2Rx55JPPmzWPatGnMnz+fvfbaq05bI2kg8JpDHU2fPp0f/ehHrF27\nFoB169Z1GPvCCy/wlre8haFDh7JgwQKefLL9J+lOnjyZO+64g/Xr17Nx40ZuvPHG19cdeuihfPOb\n33x9+YEHHgDg8ccfZ+LEiXz+859n8uTJPPzww/XYPEkDSL8+c9hat3h1ZO+99+aLX/wiBx10EIMH\nD2a//fbrMPb444/nQx/6EBMnTqS1tbXDI/vRo0dz9tlnM2XKFIYPH85ee+3FDjvsAMCll17K6aef\nzj777MPGjRt53/vex7e//W2+/vWvs2DBAgYNGsTee+/N4YcfvlW2V1L/FW3DHH1Na2trqv5nP8uX\nL+dd73pXg1q09WzYsIFtt92WjRs3cswxx/CJT3yCY445Zovq7K99JfV3W/I9h4i4L6XUWkusw0p9\nwLnnnsukSZOYMGECY8eOZebMmY1ukqR+rl8PK/UXF198caObIGmA6XdnDn11mKw32UeSutKvksOw\nYcNYu3atO79OtP0/B78YJ6kz/WpYacyYMaxatYo1a9Y0uilNre0/wUlSR/pVchg6dKj/3UyS6qBf\nDStJkurD5CBJKjE5SJJKak4OETE4Iu6PiFvy8tiIuCciVkTEdRHxhly+TV5ekde3VNTxhVz+SEQc\nVlE+I5etiIjZ9ds8SVJPdOfM4UxgecXyV4FLUkrvBNYDp+TyU4D1ufySHEdEjAeOA/YGZgDfygln\nMHAZcDgwHvhYjpUkNUhNySEixgBHAt/NywFMB27IIXOBtmc6HJ2XyesPyfFHA9emlF5JKf0GWAFM\nydOKlNLKlNKfgGtzrCSpQWo9c/g68A9A2z80HgH8PqW0MS+vAkbn+dHA0wB5/Qs5/vXyqtd0VF4S\nEadFxOKIWOx3GSRp6+kyOUTEB4HnUkr39UJ7OpVSuiKl1JpSah01alSjmyNJ/VYtX4KbBhwVEUcA\nw4DtgW8AO0bEkHx2MAZYneNXA7sCqyJiCLADsLaivE3lazoqlyQ1QJdnDimlL6SUxqSUWiguKN+e\nUjoeWADMymEnATfl+ZvzMnn97al42NHNwHH5bqaxwDhgEXAvMC7f/fSG/B4312XrJEk9siWPz/g8\ncG1EXADcD1yZy68Evh8RK4B1FDt7UkrLIuJ64CFgI3B6SulVgIg4A5gPDAbmpJSWbUG7JElbqFvJ\nIaX0C+AXeX4lxZ1G1TEvA8d28PoLgQvbKZ8HzOtOWyRJW4/fkJYklZgcJEklJgdJUonJQZJUYnKQ\nJJWYHCRJJSYHSVKJyUGSVGJykCSVmBwkSSUmB0lSiclBklRicpAklZgcJEklJgdJUonJQZJUYnKQ\nJJWYHCRJJSYHSVKJyUGSVGJykCSVmBwkSSUmB0lSiclBklRicpAklZgcJEklJgdJUonJQZJUYnKQ\nJJWYHCRJJSYHSVKJyUGSVDKk0Q2QpGbXMvvWzZafuOjIBrWk93jmIEkqMTlIkkpMDpKkEpODJKnE\n5CBJKukyOUTEsIhYFBG/iohlEfHlXD42Iu6JiBURcV1EvCGXb5OXV+T1LRV1fSGXPxIRh1WUz8hl\nKyJidv03U5LUHbWcObwCTE8p7QtMAmZExFTgq8AlKaV3AuuBU3L8KcD6XH5JjiMixgPHAXsDM4Bv\nRcTgiBgMXAYcDowHPpZjJUkN0mVySIUNeXFonhIwHbghl88FZub5o/Myef0hERG5/NqU0isppd8A\nK4ApeVqRUlqZUvoTcG2OlSQ1SE3XHPIR/gPAc8BtwOPA71NKG3PIKmB0nh8NPA2Q178AjKgsr3pN\nR+XtteO0iFgcEYvXrFlTS9MlST1QU3JIKb2aUpoEjKE40t9rq7aq43ZckVJqTSm1jho1qhFNkKQB\noVt3K6WUfg8sAN4D7BgRbY/fGAOszvOrgV0B8vodgLWV5VWv6ahcktQgtdytNCoidszzbwQ+ACyn\nSBKzcthJwE15/ua8TF5/e0op5fLj8t1MY4FxwCLgXmBcvvvpDRQXrW+ux8ZJknqmlgfv7QLMzXcV\nDQKuTyndEhEPAddGxAXA/cCVOf5K4PsRsQJYR7GzJ6W0LCKuBx4CNgKnp5ReBYiIM4D5wGBgTkpp\nWd22UJLUbV0mh5TSUmC/dspXUlx/qC5/GTi2g7ouBC5sp3weMK+G9kqSeoHfkJYklZgcJEklJgdJ\nUonJQZJUYnKQJJWYHCRJJSYHSVKJyUGSVGJykCSVmBwkSSUmB0lSiclBklRicpAklZgcJEklJgdJ\nUonJQZJUYnKQJJWYHCRJJSYHSVKJyUGSVGJykCSVmBwkSSUmB0lSiclBklRicpAklZgcJEklJgdJ\nUonJQZJUYnKQJJWYHCRJJSYHSVKJyUGSVGJykCSVmBwkSSVDGt0ASZ1rmX3rZstPXHRkg1qigcTk\nIKnXmfCan8NKkqSSLpNDROwaEQsi4qGIWBYRZ+by4RFxW0Q8ln/ulMsjIi6NiBURsTQi9q+o66Qc\n/1hEnFRR/u6IeDC/5tKIiK2xsZKk2tRy5rAR+FxKaTwwFTg9IsYDs4Gfp5TGAT/PywCHA+PydBpw\nORTJBDgHOACYApzTllByzKkVr5ux5ZsmSeqpLpNDSumZlNKSPP8SsBwYDRwNzM1hc4GZef5o4OpU\nWAjsGBG7AIcBt6WU1qWU1gO3ATPyuu1TSgtTSgm4uqIuSVIDdOuaQ0S0APsB9wA7p5Seyat+B+yc\n50cDT1e8bFUu66x8VTvl7b3/aRGxOCIWr1mzpjtNlyR1Q83JISK2BW4E/i6l9GLlunzEn+rctpKU\n0hUppdaUUuuoUaO29ttJ0oBVU3KIiKEUieGalNKPc/GzeUiI/PO5XL4a2LXi5WNyWWflY9oplyQ1\nSC13KwVwJbA8pfS1ilU3A213HJ0E3FRRfmK+a2kq8EIefpoPHBoRO+UL0YcC8/O6FyNian6vEyvq\nkiQ1QC1fgpsGnAA8GBEP5LKzgYuA6yPiFOBJ4KN53TzgCGAF8Afg4wAppXURcT5wb447L6W0Ls9/\nCrgKeCPw0zxJkhqky+SQUroL6Oh7B4e0E5+A0zuoaw4wp53yxcCErtoiSeodfkNaklTis5WkAaD6\nWUbg84zUOc8cJEklJgdJUonJQZJUYnKQJJWYHCRJJd6tJDWQ/xFNzcozB0lSiclBklTisJKkunKo\nrH/wzEGSVOKZg7SV+MgK9WWeOUiSSjxzkFQzrycMHJ45SJJKPHOQ1G95ptNzJgcNOO4wpK45rCRJ\nKjE5SJJKHFaS2uHQkwY6k4P6FXfqUn2YHKR+wKSoevOagySpxOQgSSpxWEnSgOaQXPs8c5AklXjm\nIKnp1PK4cx+JvnWZHKQecMek/s7kMIA51iqpI15zkCSVeOYgCXCoTJvzzEGSVOKZg3qF1zekvsXk\nIEm9oK8N2zmsJEkq8cyhD2q2I5B6DBk12zZJA53JoUbuvCQNJF0mh4iYA3wQeC6lNCGXDQeuA1qA\nJ4CPppTWR0QA3wCOAP4AnJxSWpJfcxLwpVztBSmlubn83cBVwBuBecCZKaVUp+3TFmqmC8kmaKn3\n1HLN4SpgRlXZbODnKaVxwM/zMsDhwLg8nQZcDq8nk3OAA4ApwDkRsVN+zeXAqRWvq34vSVIv6zI5\npJTuBNZVFR8NzM3zc4GZFeVXp8JCYMeI2AU4DLgtpbQupbQeuA2Ykddtn1JamM8Wrq6oS5LUID29\n5rBzSumZPP87YOc8Pxp4uiJuVS7rrHxVO+XtiojTKM5I2G233XrY9ObXTEM5kgamLb4gnVJKEdEr\n1whSSlcAVwC0trZ6XaITjs9L2hI9TQ7PRsQuKaVn8tDQc7l8NbBrRdyYXLYaOLiq/Be5fEw78ZLU\np/S3M/6efgnuZuCkPH8ScFNF+YlRmAq8kIef5gOHRsRO+UL0ocD8vO7FiJia73Q6saIuSVKD1HIr\n6/+hOOofGRGrKO46ugi4PiJOAZ4EPprD51HcxrqC4lbWjwOklNZFxPnAvTnuvJRS20XuT7HpVtaf\n5qlP6m9HDpIGri6TQ0rpYx2sOqSd2ASc3kE9c4A57ZQvBiZ01Q5JUu/x2UqSpBIfn4F39khSNc8c\nJEklJgdJUonDSr3MO5ok9QWeOUiSSkwOkqQSk4MkqcTkIEkqMTlIkkpMDpKkEpODJKnE5CBJKjE5\nSJJKTA6SpBKTgySpxOQgSSoZEA/e82F3ktQ9njlIkkpMDpKkEpODJKnE5CBJKjE5SJJKTA6SpBKT\ngySpxOQgSSoxOUiSSkwOkqQSk4MkqWRAPFtJkvqC6ufAQeOeBeeZgySpxOQgSSrp88NKPo5bkurP\nMwdJUonJQZJU0ueHlSRJm6vHcLtnDpKkkqZJDhExIyIeiYgVETG70e2RpIGsKZJDRAwGLgMOB8YD\nH4uI8Y1tlSQNXE2RHIApwIqU0sqU0p+Aa4GjG9wmSRqwIqXU6DYQEbOAGSmlT+blE4ADUkpnVMWd\nBpyWF/cEHqlYPRJ4vou3qkdMb71PvWKaqS31immmttQS00xtqSWmmdpSS0wztaVeMVvrfXZPKY3q\n4jWFlFLDJ2AW8N2K5ROAf+1mHYt7I6a33megtrc/blMztcX29o2Y3mxLR1OzDCutBnatWB6TyyRJ\nDdAsyeFeYFxEjI2INwDHATc3uE2SNGA1xZfgUkobI+IMYD4wGJiTUlrWzWqu6KWY3nqfesU0U1vq\nFdNMbaklppnaUktMM7Wllphmaku9YnqzLe1qigvSkqTm0izDSpKkJmJykCSVmBwkSSUmB0lSiclB\nRMRb6lTPiHrUI6kJ9PTbc31xAkY06H13AC4CHgbWAWuB5blsxxpe/1Nge+Afge8Df121/lv551uB\nyykeYjgCOBd4ELge2CXHDK+aRgBPADsBw3PMjKq2XwksBX4I7JzLLwJG5vlWYCWwAngSOAhYAnwJ\neEcn29UKLAB+QPElyNuAFyi+97JfjtkWOA9YltetARYCJ1fUMwT4G+DfczuX5j77W2BoDf17BcUt\n1H8DnA9Mq1r/pfzzTcA/AH8PDANOpvg+zj8B23ZS/6NVy/tUzA/N/XQz8BXgTbn8jIr+fSdwJ/B7\n4B5gYi7/MfDfOnpv4O3AHOCC3I//G/g18COgJccMAj4B3Ar8Kv/ergUOrkf/Alfkn32qf7vq2zr3\nb5f7B+r0+e/O1CfPHCJiRsX8DhFxZUQsjYgfRsTOufyiiBiZ51sjYiVwT0Q8GREH5fIlEfGliHhH\nJ+/VGhELIuIHEbFrRNwWES9ExL0RsV9EbBsR50XEsly+JiIWRsTJFdVcD6yn+IMYnlIaAbw/l12f\n32f/DqZ3A5OA7wEB3AgcFxE3RsQ2uf6p+edVwEPA0xQ73T8CRwD/AXw7xzwP3FcxLQZGU/zRLs4x\nX6lo+78AzwAfothpfyeXH5lSantmyz8Df5VSeifwgfyanYAdgQURsSgiPhsRb6vq3m9RfPBvBX4J\nfCeltAMwO68DuIYi8RwGfBm4lOLxKu+PiLZ2fj/30bl5e4/IsftSJB4iYngH04gc/x2KpLYWuDQi\nvlbRzg9X9O/OwNjc5ta87UHxoSQiXoqIF/P0UkS8BLyjrbyinjYXUeyc/gV4I5t+T/+9on+/AVyS\nUtoR+HxFzAHATOCpiLg+Io7JXyJtcxXF72wDRUJ9mOLJx/9OsVODIvHvRrHjWQDcksu+FBGfrqV/\na+hb+mD/dtW39ezfLvcP1O/zX7vuZpNmmIAlFfPfpcjcuwOfBf4tlz9YEbMAmJzn9yA/bwT4DXAx\n8BSwKL/+bVXvtSj/wj+WO31WLj8E+E/gJoojnDHAWcD/BMYBc4Gv5NhHOtmWR/LPV4Hbc1urpz8C\nD1S97ovA3RRHCEty2f0V65+qin8g//wcxR/vxIp1v+mkf6vft62e5cCQPL+wKubBqjr+gmJn/7u8\nPafV0N77889fVZXfmzYdkT2c5zc7cqyKf7Sif1fm33nb1Lb8J2BpxWuGUJxN/BjYpqItbdseeVui\nYnlpnr8UuJp8htVB/1Zu9wPko++qeh6p3uaK5aWV9VAcVZ4AzKM4s/oecGiN/bu0qnxh/rkNsLyW\n/u2qb6vfpy/0b1d9242/31r6t5b9Q10+/92ZGr6j78lEHXZe7dTTox0Yte28/h/F6XLlH/TOFEcp\nP8vLvwbGdbC9T+ftGVRVfjLFcMuTeflXFesuaG+b8/wYilPfrwHbASurYldRJLrPUXzIo2Jd24fr\n03m7plMcUX6D4sjwyxRHmkva2Y7BwAzge3n5Pyl2YsdSDEfNzOUHsSmB/xI4MM8fBcxv54OzMNcx\nqGLdIOCvgHvy8mPAbp3078PtlJ9D8QF8rPpvjeJb/JWxlX3/bopE/5ncjur+XUlxtPwR8g6iuh7g\nQoojwbcDZwN/R3EA9HHgluq/34rXj6AY7rmd4sxwD4pH4j8PtOaYd1b8Hu8jD/0B+wN3VtT1UC39\n21Xf5p+93b/HbEn/dtW3FX23BzB5C/u3lv3Dln7+l1ZvT1dTw3f0PZmow86rkw9Xt3Zg1Lbz2gn4\nKsVp53qKccXluaxtnH8WsGcH2zuTYvjlL9tZN4NNH67zaGeMNP+x3tBO+VEUH/zfVZWfUzWNyuVv\nBa6uiDsYuI4iST5IcXR1GsU477U1/B73pXhkyk+BvfLv6Pf5D/69FTGLcr/d1dZHwCjgM3m+Jbfj\nOYoj2Ufz/HXA2BxzOrBvB+34NMXw04x21n0S+HOe/24H/fsO4K6qskEUO6//AH5bte57VVPbdZy3\nAj+viDuZYuf7PPASxZDBV4Ad8vo729ueitcfQvFY++XAgRRDEo/lvjk6x0ynOHN+jOJI/4CK/v2n\nqv5dk/u2rY7rKIaAOu3b/LM3+/eqGvv34x31b1d9W0P/tu0n2vp3Re7fqe30by37h7p//rvcvu6+\noBkmtnzn1XZGscU7MGAfNt957VHxy/9MRT17AX9Z/ctj84u/e+U/uHZjOll/eK11VMdQjMNO6G5b\ntrC9lXW8q8aYrvruAIoj5BHANOB/AEdUxU9h0/DieIoDjCNqXd9JzJFsfoBSGfMXwP9qp54Duvle\ne1McDHV3mw6oqqO9fnlPV22piB2Rpx908bm5urP13Y2p7N+q9bsAa+v0Xt+vQx23UD7CD/LF71rq\nyX8znyMPX3UQc2D+PW1RTGdTv3u2UkR8PKX0vWaIaVsfEZ+hOLpaTnFh78yU0k05ZklKaf+uYiiO\ngM7ooo5P1xBTS1u2uJ4a2/sZ4FMUR0xbEnMOxXWhIRR3PE0BfkFxcXx+SunCdmIOoBg+/ABF8h/S\n2fpa6uggppa21Cumq23q6fu094Tk6RRDO+0JiguqtwOklI5qp456xWzWlnrF9HCbetqWRSmlKQAR\n8UmKz9W/UYxY/N+U0kVVMafmmJ90N6aDbWtfTzJKM09UXRdoZEzbeoqzlm3zfAvFcNSZefn+WmLq\nUUdvxjSgLYMpboV8Edg+l7+RTcOMncbUo45mi6nj+yyhGBY6mGI49WCKO9gOytP9na2v+JuoR0yn\nbalXPb28TZXXNe9l00jIm9l0fbQuMd2ZmuKR3d0VEUs7WkVxIafXYmqpg+I0cwNASumJiDgYuCEi\nds9xtcTUo47ejOnNtmxMKb0K/CEiHk8pvZjj/xgRr9UYk+pQR7PF1GubWoEzKe6Q+fuU0gMR8ceU\n0h0AUdxu3eH6rF4xnbalXvX08jYNioidKK6jREppTf4d/P+I2FjnmNp1N5s0wwQ8SzHEsHvV1EK+\nONVbMTXWcTswqWobhlDckvdqLTH1qKM3Y3q5Lfew6ctNlXfU7MCm2/w6jalHHc0WU6/3qShru8vt\nX2nnrLmr9X0xpjfeh+JLqG23/q5k0xdWt2XT3Zd1ienO1PAdfU8mii+RHNjBuh/2ZkyNdYwB3tpB\nzLRaYupRR2/G9HJbtulg/Ug2fZu405h61NFsMfV6n3bWHUn+Dk9P1vfFmN5sS0Xsm8h3223tmPam\nfndBWpK05frk4zMkSVuXyUGSVGJykCSVmBykLCJaIuLXPXzt2yLihk7Wt0bEpV3UsWNEfKon7y/V\nmxekpSwiWigeajdhIL6/VMkzB2lzQyLimohYHhE3RMSbIuKJiPjHiHggIhZH8X825kfE4xHxt9D1\nWUdEHBwRt+T5cyNiTkT8IiJW5keEQPG/B96R3+eft/6mSh3rk9+QlraiPYFTUkp3R8Qciuc6QfHF\npUkRcQnFUz+nUfy3sl/Tk3+kUjyU8P0Uj0x/JCIup/gnRxNSSpO2cBukLWZykDb3dErp7jz/A4rH\nQkPxbyZh07OeXgJeiohXImLHHrzPrSmlV4BXIuI5Nj1qRWoKDitJm6u+CNe2/Er++VrFfNtyTw6y\nKut4tYd1SFuNyUHa3G4R8Z48/9cU/6Ojt7xEMcwkNZzJQdrcI8DpEbGc4j90Xd5bb5xSWgvcHRG/\n9oK0Gs1bWSVJJZ45SJJKvAgm1VFEHEbxj+Er/SaldEwj2iP1lMNKkqQSh5UkSSUmB0lSiclBklRi\ncpAklfwXG+X4LcTNJbAAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYcAAAEGCAYAAACO8lkDAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#平均医疗开销分析\n",
    "print('平均医疗开销分析：')\n",
    "for v in variables:\n",
    "    group_df = df.groupby(pd.Grouper(key=v)).mean()\n",
    "    group_df = group_df.sort_index()\n",
    "    group_df.plot(y = ['charges'],kind = 'bar')\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "_cell_guid": "078f27b3-a846-47c8-a7d8-5412d44b3fbd",
    "_uuid": "109f80eba0b4c3fc6f6479a805b94fed55dbf3cb"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "两两变量分析：\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAs8AAALICAYAAACAdx0PAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nGo2mg/x//q5R22nNomAAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 720x720 with 20 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#两两变量分析\n",
    "print('两两变量分析：')\n",
    "variables = ['sex','smoker','region','age','bmi_int','children','charges']\n",
    "sns_plot = sns.pairplot(df[variables])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 步骤 3：构建模型"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "_cell_guid": "bdf90848-3c21-4d3c-91be-2e30ecc6d7d8",
    "_uuid": "f97e66a90b2bb51c02190aa3620ed716b86a343d"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "建模与评估\n",
      "\n",
      "\n"
     ]
    }
   ],
   "source": [
    "print('建模与评估\\n\\n')\n",
    "\n",
    "#对类别型变量进行编码\n",
    "le_sex = LabelEncoder()\n",
    "le_smoker = LabelEncoder()\n",
    "le_region = LabelEncoder()\n",
    "\n",
    "df['sex'] = le_sex.fit_transform(df['sex'])\n",
    "df['smoker'] = le_smoker.fit_transform(df['smoker'])\n",
    "df['region'] = le_region.fit_transform(df['region'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### **任务二：选出实际建模时所用的特征与标签，并对数据进行标准化处理**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# YOUR CODE BELOW\n",
    "\n",
    "variables = [\"sex\",\"smoker\",\"region\",\"age\",\"bmi_int\",\"children\"]                       # 选择特征\n",
    "\n",
    "X = df[variables]                               # 导入特征数据\n",
    "\n",
    "sc = StandardScaler()\n",
    "\n",
    "X_scaler = sc.fit(X)                                 # 对数据标准化处理\n",
    "\n",
    "X = X_scaler.transform(X)\n",
    "\n",
    "Y = df[\"charges\"]                               # 导入标签数据\n",
    "\n",
    "\n",
    "\n",
    "# 使用sklearn.model_selection库自动对数据进行训练集与测试集的分割\n",
    "\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, Y, test_size=0.2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### **任务三：构建模型，并进行训练、测试和评估**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "regressor =  RandomForestRegressor(n_estimators=200)\n",
    "regressor = regressor.fit(X,Y)\n",
    "\n",
    "y_train_pred = regressor.predict(X_train) \n",
    "y_test_pred =  regressor.predict(X_test) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "RandomForestRegressor evaluating result:\n",
      "Train MAE:  1207.5494589794764\n",
      "Train RMSE:  2221.1303822866917\n",
      "Test MAE:  1207.5494589794764\n",
      "Test RMSE:  2221.1303822866917\n"
     ]
    }
   ],
   "source": [
    "#计算相应的MAE和RMSE，填入计算需要的值到括号中\n",
    "print('RandomForestRegressor evaluating result:')\n",
    "print(\"Train MAE: \", sklearn.metrics.mean_absolute_error(y_test,y_test_pred ))\n",
    "print(\"Train RMSE: \", np.sqrt(sklearn.metrics.mean_squared_error( y_test,y_test_pred)))\n",
    "print(\"Test MAE: \", sklearn.metrics.mean_absolute_error(y_test,y_test_pred ))\n",
    "print(\"Test RMSE: \", np.sqrt(sklearn.metrics.mean_squared_error(y_test,y_test_pred)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "_cell_guid": "0d024932-ba9e-47aa-9e92-893b37d5c420",
    "_uuid": "9e7392173889c190c75d1d87ff1ee672cda9aa12",
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "特征重要度排序\n",
      "\n",
      "\n",
      "1.smoker(0.621435)\n",
      "2.bmi_int(0.190265)\n",
      "3.age(0.138344)\n",
      "4.children(0.022577)\n",
      "5.region(0.018977)\n",
      "6.sex(0.008402)\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXcAAAEJCAYAAABv6GdPAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nrkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 简单可视化模型，查看各个特征在随机森林中的重要度\n",
    "print('特征重要度排序\\n\\n')\n",
    "importances = regressor.feature_importances_\n",
    "std = np.std([tree.feature_importances_ for tree in regressor.estimators_],axis=0)\n",
    "indices = np.argsort(importances)[::-1]\n",
    "\n",
    "importance_list = []\n",
    "for f in range(X.shape[1]):\n",
    "    variable = variables[indices[f]]\n",
    "    importance_list.append(variable)\n",
    "    print(\"%d.%s(%f)\" % (f + 1, variable, importances[indices[f]]))\n",
    "\n",
    "# Plot the feature importances of the forest\n",
    "plt.figure()\n",
    "plt.title(\"Feature importance\")\n",
    "plt.bar(importance_list, importances[indices],\n",
    "       color=\"r\", yerr=std[indices], align=\"center\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 步骤 4：使用模型预测"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### **任务四：在新数据上进行预测**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {
    "_cell_guid": "35dcf7ff-9e8d-4090-b4ca-8910d610fc3a",
    "_uuid": "834b9c0f72d55e8db00fdf7c6e611cc87557fbb9"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "在新数据上进行预测\n",
      "\n",
      "\n",
      "Billy -  ['male', 'yes', 'southeast', 25, 30.5, 2]\n",
      "Billy的医疗开销 =  35143.159769249956 \n",
      "\n",
      "\n",
      "Dennis -  ['female', 'no', 'southeast', 45, 19, 0]\n",
      "Dennis的医疗开销 =  10455.822990733333\n"
     ]
    }
   ],
   "source": [
    "print('在新数据上进行预测\\n\\n')\n",
    "\n",
    "# 构建新数据\n",
    "billy = ['male','yes','southeast',25,30.5,2]\n",
    "print('Billy - ',str(billy))\n",
    "\n",
    "# 对数据进行标准化处理，注意这里要用与训练时相同的模型，不可重新fit\n",
    "# 另外注意，这里的函数输入的是一列，返回的也是列，故需要添加[]，同时返回值也需要提取数据\n",
    "billy[0] = le_sex.transform([billy[0]])[0] \n",
    "billy[1] = le_smoker.transform([billy[1]])[0] \n",
    "billy[2] = le_region.transform([billy[2]])[0] \n",
    "\n",
    "# 与上边同理\n",
    "X = sc.transform([billy])\n",
    "\n",
    "# 对新数据进行预测\n",
    "cost_for_billy = regressor.predict(X)[0]\n",
    "print('Billy的医疗开销 = ',cost_for_billy,'\\n\\n')\n",
    "\n",
    "# 第二个新数据，理解上边的注释，仿写\n",
    "dennis = ['female','no','southeast',45,19,0]\n",
    "print('Dennis - ',str(dennis))\n",
    "\n",
    "dennis[0] =  le_sex.transform([dennis[0]])[0] # YOUR CODE HERE\n",
    "dennis[1] =  le_smoker.transform([dennis[1]])[0] # YOUR CODE HERE\n",
    "dennis[2] =  le_region.transform([dennis[2]])[0] # YOUR CODE HERE\n",
    "\n",
    "X = sc.transform([dennis])                  # YOUR CODE HERE\n",
    "\n",
    "cost_for_dennis = cost_for_billy = regressor.predict(X)[0]      # YOUR CODE HERE\n",
    "\n",
    "print('Dennis的医疗开销 = ',cost_for_dennis)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "作者：寒小阳、助教Choc\n",
    "\n",
    "本文档版权归稀牛学院所有"
   ]
  },
  {
   "attachments": {
    "image.png": {
     "image/png": "iVBORw0KGgoAAAANSUhEUgAABmsAAAEUCAYAAADECQLvAAAgAElEQVR4AezdCXhcV3k38Pc9s0nyFstxdgglCVBCSGyZLI7kKNSQ2JIDodgfBcKS0iaQ2FmghEALoi0FSkhi2QHSsrWssSGQxTZLW1TbcQixJIdgCHsg0Dhkj21ptnve7zmyRp4Zzcw9d5lV//s8fmbuvWf93fFIuuee9xBhgwAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIBACQEucQyHaizQP7jnTCF948E5zy4fevv5yRpXj+ogAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCoo4CqY92omoj6NoxcJKSHiOjcWfvnDQAFAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIACBmSWAmTV1vN79g6NvEpL/JKLcoJmjlD7zriuXjNSxWagaAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIACBGgrkBglqWCWqMgL9gyOvLxqoMYcjWtTnegd+EIUSBCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACM0MAgzV1uM4rb959lhB9NW9GzeFWCJ0xq/OI9x4+gHcQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQi0sgDCoNX46q66YfeRTlyNMNHzKlSdUqzPuGvtkocqpMEpCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEWkAAM2tqfBElFvmCy0CNaVFCS+TfBwYE16fG1wfVQQACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAARqLYDBgBqK920YuUhY+u2qlO7dnSPvskuLVBCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCDSrAMKg1ejKrd60KTL22Cm/IJEXeqjygBJ96l1XLfm9hzxICgEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAQBMJRJuorU3d1IOPnfxa9jZQY/o7W7O6lYhWNGvnL7hxb2c0mvrwlnWL1zZrH9BuCEAAAhCAAAQgAAEIQMC/wLmfe/EciXQs0qyXMHEXEXWR8FfvfdvoP/ovFTkhAAEIQAACEIAABCDQWgIYrKnR9WShy31WdeHK9SOXbL1q8Zd85q9rtlgs+Q4RvrJ//ei2u69atLWujUHlEIAABCAAAQhAAAIQgEBVBUoNzGihFxEJsxwO7MCC9TmreiFQOAQgAAEIQAACEIBA0wkc/m256ZrePA1edevuDp1STxNR3Gern9BEL922bvHjPvPXJdvAgKj7O0d/TUQvEKJHZkUSL918xakH6tIYVAoBCEAAAhCAAAQgAAEIhCpQamCGJgZmyPXvTBb68K637xkItUEoDAIQgAAEIAABCEAAAk0sgJk1Nbh4Ohk9i1j7HagxLTxSkdxERG+uQXNDq+JH8/esYqIXmAKZ6Hlj2dR7ieiDoVWAgiAAAQhAAAIQgAAEIACBmgiUGpgpNWOmJo1BJRCAAAQgAAEIQAACEGhBAQzW1OCiCsuJro+WubaD37Riw8hXtq1dvM01aYMkYJYrC5rCdO2qG3YP3vWeJU8UHMcOBCAAAQhAAAIQgAAEINAwAhiYaZhLgYZAAAIQgAAEIAABCMwgAQzW1OBiM+kjJuaWBKxLCX1m9S17T22GUGJ9Nw3/OREtL+ryLImpdxPR9UXHsQsBCEAAAhCAAAQgAAEI1EEAAzN1QEeVEIAABCAAAQhAAAIQKCGAwZoSKGEfEmIdfGbNRKueP+6kPkJEV4XdxrDL44i6QkimFStMl626dfc/3XXZkrFpJ3EAAhCAAAQgAAEIQAACEKiaAAZmqkaLgiEAAQhAAAIQgAAEIBBYAIM1gQndC1BE/zd92MI9X6kUQrR2xeDw17at6/phqfONcGzF4A/nCslby7RlvpOKrCGiL5Y5j8MQgAAEIAABCEAAAhCAQEABDMwEBER2CEAAAhCAAAQgAAEI1FgAgzU1AM/qyIMR5YRVEyviz64e2Lt488Cp6bAKDbMcpvjbiGh2uTKZ5A0YrCmng+MQgAAEIAABCEAAAhDwJoCBGW9eSA0BCEAAAhCAAAQgAIFGFMBgTQ2uytnPvPyX93eOPkpEx4ZU3aljnan3EdE/hlReeMWIMG8YvcKlwOWrb9k7uxnW3nHpB05DAAIQgAAEIAABCECgpgIYmKkpNyqDAAQgAAEIQAACEIBAzQQwWFMD6oEB1n0bRr5BQmtDrO4DfTcNb95yTdfPQiwzcFF9G0deTcQvcikocjCb7Cai77ikw2kIQAACEIAABCAAAQjMWAEMzMzYS4+OQwACEIAABCAAAQjMQAEM1tToojtO5JaIcq4kIg6pyjhF+LMDA9JjBoNCKjNwMazVlcLuK/Sw4ldgsCYwNwqAAAQgAAEIQAACEGgRAQzMtMiFRDcgAAEIQAACEIAABCDgUwCDNT7hvGb7ztWn/7xvcHQzkazxmrdC+qU/mj/yTiK6pUKamp3qu+n+FwpLn02FInSyTTqkgQAEIAABCEAAAhCAQKsJYGCm1a4o+gMBCEAAAhCAAAQgAIHgAhisCW5oXYIS5+80q34i6rDO5JKQmT76mlt+dOcdV5z5iEtSX6cvuvnBo51I+lXi8O+3Xr14e6VCJBK5gi1nDjHR8yuVhXMQgAAEIAABCEAAAhBoBQEMzLTCVUQfIAABCEAAAhCAAAQgUH0BDNZU33iqhruuWvL7/sHh64R4w9TBwG94jpONfYqIVgUuyhRy6+6ObFqdpzS/iliWO5Q5jYSJFWX6NwxfcvfarttK1fPqTzwwi8m5tNS5UsfEclCnVF4cgwAEIAABCEAAAhCAQCMKYGCmEa9K67ept7f3iNbvZXP3cGho6Fkico8XXsVu9vb2mvs/s6tYBYomokwm49xzzz37643R29vbRkTmH7Y6CjTj//0gbcbPI38ftkb53ihufW9vr/mZ4WvsYP/+/QeHh4czxWX62Q/yuQryec5va5CfoV6vry/w/MbivTeBu9cuvqVvw+hyInqNt5zlUwtLf9/6kTdsuWrx18unKn9m5caRE8mRfmbu1yk6XxElaPq6MzER/nrf4PCxW9Z13VxcWiyefRMRW/+RwESh/Ictbgf2IQABCEAAAhCAAAQgUAsBDMzUQhl12Ag4jvO0TTqkqZ9Ab2/v/KGhoWfq1wKibDbbzcw/qGcbZkLdSqkHiOiMevdVa/0+EflQvdsx0+tvhP/7juO8lIjM59JqW7Zs2Yu2b9/+S6vERYnw86gIxHK3Ub43ipurtV4vItYP5ufnnzVr1vVE9LH8Y37fB/lchfV/UGt9lYjc4KcPSqkvE9EltnkxWGMrFVY6Zol8/KFLnPaxHUR0eljFEtPgxRvv+/63rjzrSdcyRXjV+j1LnIhczCKrSNPLiNk126EEfNPKDSNHbV27+P0FGZjWFuy77sgfXJMgAQQgAAEIQAACEIAABBpAAAMzDXAR0AQIQAACEIAABDwLRCKRnzqOk7SdaSUiXUTka7DGc+OQoaEFtNabmdnXYI2IrA5rsKYRkCb746spIrLJS0YM1njRCintnde9ZP+KwQf6FTlDRHRSSMUuTEvsk0T0tlLlDQyIur9z5FwSdbFsGH29VvS8Q5NnbAdpDpfKQtevXD8yf+u6Re8iZlk1OHKeJnrZ4RQ27xS++G2YkAYCEIAABCAAAQhAoKYCGJipKTcqgwAEIAABCECgigJDQ0PZnp4eM7PmLMtqzGCNr8g9luUjWZMIjI+P/3dHR4eZvTvfR5MXL1269KRdu3b92kfehsrS3d1t1l23/f9T3Pbn5syZ873ig5X2MVhTSaeK57atO/0PKwYf6A11wEborSs3jn5l65WLvp9r+sqbd5+llHrj/TS6moiPNeHNvA/P5Eo7/MpMl/dtGGnr2LTpHWP7aN3hM5bvhMxAFTYIeBHgaHv7uSQS6vdWNhrdSwcOPO6lIZNpE9G2trOpiusvKa2fSqfTP/bRthmRpa2t7QVZoheE1Vl2nGcymcyesMpDOcEFou3t3WH+n48SPZxMJh8O3jKU0PACc+YcGc1kPD5IUrlX2VjsQdq/330Gc+VicLbBBDAw02AXBM2BAAQgAAEIQCB0AWYeFhGrm82TM2tCbwMKbD4Bs+bMsmXLvuU3FJpS6vVE9PHm63lhi5VSq0V8Lzt357Zt21KFJVbeC/WmZ+WqcLZYwAzYXLRhZFlWaBsTvbz4vJ991vJvKwb3vE6JvpiY3mhm7vj+OLk2gN82tu/kTiLqc02al0CIHjnz6TN+uCXvGN5CwEJAOJtNilKfJ6LTLNJbJYlmMvspHv9YNp2+iYjGbTJF4vHVxPyvJBLaQEFxvSLyhXQ8/j5Kp4tPYX9SICvyTiJ6b1ggopQZ6H51WOWhnBAEtDZx1UP7XSXD/BYiwmBNCJem0YuIZTKvEZHPhthOTVofF2J5KKoOAhiYqQM6qoQABCAAAQhAoO4CWuthtlz+gJnNzBrznHf1bifWXQQNsBUIEgqNmS9uhcGaWoZAM9cltBsgthcZ6QoF7ly7+P+W37p7WVtKfU2IVhSe9bX3AkV6JJTpM3bVX2SX7HAqJlo/MMD68BG8g4CdQCaT2U1EXdG2tg+QyAdC+g6bQ8wfiSYS7xTm9zvJ5FeIqOTnMxaLLRGlzKBOt12LfaRiNr9EXZEdH78PAzWV/YRoQRgzBXO1MPNTufd4bQCBOXMWUDod6u8pMaJ7nAboGppQfQEhOiXkWr5PBw8+FnKZKK6KAhiYqSIuioYABCAAAQhAoKkEmNncS7Hd5i5btuzk7du3Y/kCW7EWThcwFNpZJoTYzp07f9+sRLUOgWacQr0J0qzw9W73f1225NnVmzatOvjYyf9k1oOpd3uqXP9vO7LJT1W5DhTf2gKZbDI5EIvFviWRyOfo0OJ3YfT4BBb5z2gicTUxvyebTJon+g9t7e3HxxznX4T5kqqFPRN5kpV6fyaZNE+ClxwsyjUHr4cEmGhBmBZaBIM1YYIGLCueSi3Ulk9/WVa1L5lM/sYyLZI1u4BIqIM1wvzVZidp5fZjYKaVry76BgEIQAACEIBAUIFIJPJTx3GSRNRmU9ZkKDQM1thgtXiaEEKhrSYis8Z6U261DoFmkDBY0yAflc1r1piHfd+/YsPIDiX0n0R0ZIM0LcxmaGa+dPO1S61CTYVZMcpqPYFMJvMAZTJnR+Px64j5g0QUD6mXi0nkf6KJxN2s9T8I82tI6/cKc0dI5RcXo4XoVied/nsiwmBBsU7l/VC/J5kZa1GU8I4mEkMcYG0gUeqvsuPj95YouuIhrdRC8h8XtlTZO0sdxLGWFTg5xJ6NO8nk7SGWh6JCEjjnP84ws2G7tNCLiIRZwpxvGVIjUUxZASHqXfqFMwbKJqhwQkj98N63j3ynQhKcggAEIAABCEBgUmBoaCjb09PzgIdF0k0otK8DEAJGIEgotMkQYk07WFPrEGjGG4M1Dfb/btvaxdtWDI68VBGZ2SdmIaaW2YTomi1rFw21TIfQkUYQyGbT6Y/E4/HbNdEXiNlqwTzLhveLUv2Waf0mu4e1XpvNZEb9FjDD85k1s0LbWASDNaU1DwjRiaVPWRx1nGVE5HmwRrQ+xjauskUrTHTQXTbp8tPE2tpuI8uFOPPz5d5roq1OKvWu3D5eayoQ2mANM99JRAdq2npUZicgE+sz2qVFqsYTYDpPiM7z1TDR64kIgzW+8JAJAhCAAARmogAzD4vl3zaTM2tmIhP6XEJgpoZCq0cINMOPwZoSH8J6H9q2bvHjRLS6b8PoahIxgzahPj1ej/4xy3Vb1nYN1qNu1Fl3gTi1tx8TIzpOO85xivkYYT5eRI5monnZVMpMiQy0pdPpnxHRudFE4loi+jARtQcqsPqZ9wnzdU4y+aUmWLSvM5pIhPFE+ceyqVTYN1XCDYPG/ET1L31T1mD+f/X5bjnzuX7yKuaFoa5oqZSnwZpEInGyI7LGT9tzeRTRA1gjJ6dRw9f29uNJ69BmQ2qRL9ew9agKAhCAAAQgAAEIQAACoQtorc36uFblMrOZWWMSh/onmVXlSNRwAjM1FFo9QqCZi4/Bmob7L3C4QVvWLtq86obdP9Bx9c9E9DdEpA6fbZp348L8ji1rFyPWe9NcMuuGticSieMcpY4WxzlhchDmONbaDMYcS0THk8gxxLyAtJ74CW9+MZj4SS8y8VOfiJ61rs09oZNNpT6RSCS+7RB9noi63bPUPEWWiDZkUykT8uO5mtfuo8JYW9vFIuLvqdfD9elsLLaGUqnDR8J5F+rMGsKaNSWvCjPvlSDhyESW+vlFX5iPCjEM2nhmfHykZAfLHHSI/rbMKevDGaW2WSdGwtAEoiKhzaohkSeddPq7oTUOBUEAAhCAAAQgAAEIQKAOAsy820O1c5ctW3by9u3bsW6NB7RWTjoTQ6HVIwSa+QxhsKbB/yfd9Z4l5knvy1feNPoZjoiZmdLT4E3Ob95zwrp769olD+YfxPuGF5idSCSOd8wMGK2PZebjiMiEIzpBRI6aGIQhMoMx8yaeGNea8gdhJP9Jjfz3Nep2KpUyv0ycF0skrhCijxLRrBpV7VbND5TIlel0+qduCRvpfJAfTnn9+G86cOBPefthvJ1NRLEwCsqVoZR6ErMgchp5r46zl1SAZwWYF8Tj8Ren0+mH8kp1fTs5+841nWWC+4koY5nWJEuQyKUU7DtsL42P/95DnUgakgATnRzWI4DCvMnjZyekXqAYCEAAAtURYOZ/0FpjHbeAvMx8BhHdFLCYhs4uIqsQBvTQJWLmtxHRWxv6ghU1Tin1xWw2izD0RS512G2YULqRSOSnjuMkiajNxmEyFFrVBmuq9fPI6/dztb7rGvF7o7e3d7bjOHfbXP8SaYLcfzmrp6enLt9Hpr89PT3mwWk/m++lFpj5+p6ennf7qRSDNX7UqpDnNbf86HlZJ/pildC77rpsyVhxFVuvWbSHRM7rHxx5rSj+CAn9eXGaBtyfy6JeTUQYrGmMi3NEPB4/Vit1vGhtQpAdT8xmEOY4ETEDMkdPDsTMmrhhbWa/5N2oDPRkfe37rzOp1Ia2tra7syJmlk1v7ZswVeMfRORaJ53ePHWked7MI6JXBm0uM98WtIzi/G1tbUdmg8z2KC7QTF3U+qkSh2f8oUwm87NoIhHIQZQyodA8DdZwmCFAme/x0oFIPP6XE7MCvWSannbr9EM4UgsBITolrHpYKbOAPTYIQAACLSMgIj/ZuXNnXW6YtAyimcLf3V3wt1Ir9S3Xl2g0unNoaOiZ3P5Mfl22bFlvk/09TENDQw8TkfmHDQITAkNDQ9menp4HiMj2BrQJhfb1avFV6+eR1+/nan3XNej3hhkHCBo5xe9Hol71+grL7reTefnOyXvv6S0GazxxhZ/4oo8/NMdpH/tA1qGrzOi2TqlM3+DIj4h5SJP+n/HZz+0aevv5ZuSbiFnuJvrWwIDcsbtz9M1C9EEiOin8VoVa4g0rB0ef3Lpu0RdDLRWFeRaIJhIPa6J5JqxQEw/CeOp3Mpn8rRlsiLW1vUNEPklEczwVECxxmphvyCaT/0JEB4MVVZ/ckba2i0gkyNMTpuHpTDL5zbB74DjOkYFme5RoUCoef6oKodpK1NR0hw4w0SNC9Dy/Lddam1+QPucxv5nBF8omIp6eIGbmdwaumBmDNYERfRYgEspgjRA97IyPe1rryGeLkQ0CEIAABCAAAQhAAAJVF2DmYRGxGqyZnFlT9TahAghAoFAAgzWFHjXbGxgQdX/n6NscGjM3cs2MhtxmboyeSyLnKuIPzNo/L9W3YeQ+1rSLFd+Xzjr3DVzDjxLRf/YO/OCrHQuOWMOiryfil+UKaLRXJvnsyo3DT2y9ssvvVLtG6xLa01wCkkkm/53a278b1do8IV2LtWy2RoiuTiWTVZsyXItLwAEXV59s4/eIKPQn8kSpcNerMQsn7t//ZC1cm7EOITLh+3wP1jCzWbfG63ak1wxl0ouTSt1b5ty0w/F4/KU6+PfE/mwy6Wk2z7SG4EAQgVDWrGFms95eWBHVgvQHeSEAAQhAAAIQgAAEIBBYQGs9nP/wbqUCmdnMrGH8PlxJCecgEL4ABmvCN3UtsX/jyDn369GNRLTYNfFE3HxaJkzLzLTbaERR3+CIiZ/vEGwAACAASURBVIF/n/knjtwfE9WTiUwM8FxFTK+yKLPWSSKsedOq9btffddVSzw93VzrhqK+lhWYH9X6Gg/TfYNAPC4iX0ml078KUkgD5DUh0EwYw0CbsQhUQJnMItJp+0tmmSIKD4u0VAi0aDz+PiZ6SWEn/e8FmVUzWeuLY21tXyOtU7atEKI/s03rku7ZWDxuHVNeM5/pUp7raSZ6OhaP/7trQpcETHRDOp3+SaVk0Xj8vcz8rkppqnVOiPZmU6m+4vIj8fhqRTTteHG6au0L0YtDKVvkzFg8XveZwZl02sTJxwaBlhMQ4Y+3kXysXMdSTL8jornlzuM4BCAAAQhAAALeBJh5t4ccc5ctW3by9u3bm/ohVA/9RVIINIQABmtqeBkuuHFvZzSa/Jho+puA1T6fiMy/1azMisliQqT9hoVGSeirwvQKCjFee8C25rK3a1ZbVm7Y3b117RKsYZNTwWu1BaKxROKdwjxAImHPxCjX9oXM/JVoW5sZHLo2m0zuKJewkY9PhkCLB2xj0kmnqzKjTjEvCPVxd+bWmlXDvEaIFgW8fqFmF5E3UN46WKEWXrmwI4S5pgvCivkZHUKdiuijlbtGJMwm5NeJbumqdL70H27My6XJFuEt47Nc6vOZzW/Os/k7eA+BVhJQJMmht+8pO/v2nC+eEeqP+layQ18gAAEIQAACfgQikchPHccxSy202eSfDIVW+nd+mwKQBgIQ8CwQ6mCNGYyIRNKvY5ZXEslpRDyHSZ4S4m+rhL7hrsuWjHluYStkEOGVg6NvZk59kogXVqVLIi8UphdWpezwCp3Lor7bd9P93VuuecVvwiu2dUpatXH34ruuXDLSOj2qX08iicRKJvqkmNkFIS9Eb9UrkSVEtD2aSHw7QnRdKpX6hVW+BkkURgg0Zr6DiA5Uo0tmZk2oN/5bbGaNEM0189WxNbWAk0qlXH9WcmEo1Zp2mJmfKFUhEx1V6jiO+RL4k69cyAQBCEAAAhCAAAQgAIEigaGhoWxPT88DHqKOmFBoXy8qBrsQgEAVBUIZrOkf3HOmkLybKPU6Ipos89BtIiE2T3sukpQ6b2BAXjUwwLqK/Wm4oi+8+YEXRzaMfJqYz2+4xtWnQcdSJPKdVTfsXnrXe5aUvMlTn2bVv9aLbhk+2XH4HURUl3A29RcIpwXxePxlmvmTYYTwCqdF9FqHqD+SSHzGicc/TPv3N8PnPpQQaFrrTSEZTitGmBeGOhjB3FJh0BhhY6Z9ZprtgFncnszkWbdN5KhQBy7d6ss7r0VKz0gTObpebcprXmu8FXm8NTqCXkAAAhCAQLMJaK37enp6DjZbu6vRXhEJLbxwNdqHMiHgUeCbRGRm19hsmOVqo4Q0EAhRINBgzYrBPYsU6Y8K6Qvc2iREr9w9f8+FRLTVLW0rnO+6dXfs6HTk/SzO+4k4aCihViDJ78MpOq7uWH3jruWbr106nn9iJr93HP6kiPx2JhsE6vvs2Qsjmcw/apoIMxgJVFb4maNMdGU0nb6E4vF/yabTgx5+OQq/NS4lhhQC7Tknnd7iUpXv04q506zjFdbG5W46h1VB7ctBjP/am4daIxM9ZFOgMB8Z6sClTaWTaVhkX8nkzEeWPI6D3gWYH/OeCTkgAAEIQAACwQVE5MvBS0EJEIBAowns2LHjE0Rk/mGDAAQaUMD3YM2qG3YfqUmbtRhm2fdLembCYI0JZaVT6vNEcrq9zYxLuXQ80valgQFZM9NmW5W60is3jr6KtFykiD5c6nyTHBtjoieFyMQeNzH2n2XmZ7WIeX2GtJ7aJ+ZnWalnlOM8HULf4tFE4irKZP6+CRahnUfMH48lEu/SIu930umvEZlFpxprCyUEmsi3ich6MXmvAiKywGueSumFuZWeXk8QkfmHrbkFrGJDM9Ex9epmuTBoVMfQbPWyqFa9QoQwaNXCRbkQgAAEIAABCEAAAhCAAAQaTMD3YI2Oq/d4G6ghIqaWftJy9cDe+Fhn8kNa83VE1GhP9jfYR88sikx/+aP5IzcS0dUN17gaNqh34AdR1vpG8x9EqG6LnJvp7RMDLJOf3Rd5JWCl/iIzPv5Dr/mCpI/E468j5huI6M+ClFPrvEJ0IjN/JdrWdjUxX5sdH99Z6zZUqC+UEGjCbAaiqrcxd4a6FlErrVkze/ZcyrhHz6rexUHJYQgwkc06V+2efxcLo3GTZZQJg2YGCjGzKyTnCgNiIdWAYiAAAQhAAAIQgAAEIAABCECgUQR8DdYcmlVDV3rthLCYJ+5bcutb/8DLxjj1ZSLGbBoPV5iZr+obHH54y7qumz1ka6mkszrn/Q0Rvcx0SlT1BmtE5J1ENG5mtLDjPBuJRJ5NJpO5WTBODjXW1vY3IvJvuX3bV6V1zdb8iMVii0Wpm4homW37fKZLE1H1whiKvIJEdkQTidsjRO9LpVJWT9L77ItVtpBCoD2RTaX+26pCn4lEpDPM0E/cQmvWJDKZuVP/oX36Ilv9BYTZfbCmvX0h6fotBchKTQ/R1d5+ZD3bVP8rF24LWOTRcEtEaRCAAATKC/T09BzLzJeVT3HoTDab/dKuXbt+7Zau+Hxvb2/UcZz3M7MqPpe/LyL7mLnizFER0WNjYx8dHh72/IRKd3f3C5VSb8mvs9R7pdRnh4aG/lDqHI5BAAIQgEBggb/u7u7uDVxKUQHMfELRoYq7juN8tLu7O/SoICJydsWKm/AkM3+8kUP6NxKpiHzIb3t8Ddb4mlVjWij8M78NbdR8AwOiftS5591Ezj9X9aZuowKE0i7+5MoNI49sXbvYLHI2o7bJgU/z2ZnYmHTpxZpzCQK8TobcmiohU+bJe9F6vp+FoVOx2NOUCv3n21R7J950dBwXyWY/IsxvnZirV3g2zD0RkS848fj10UzmDCb6rBA9L8wKisp6nUO0KppIfDobj/8j7d9ftc9BUb3TdlnkL6cd9HpAhKOJxP1es3lMH/ZsquuiiYTrzQmPbQycnJl/nkkm/5+XgrTWc0lVvAfipTikrZNA1mKwJpbNHiN1vNZK6yeKeWLZ7LH1bFNxe5p9X4tMM272PqH9EIBA4wqMjY090dHRsY6I5ldqZSQSMeFo11ZKU+qc4zj9RPRhi3UH325zk6Ojo2MvEfn5G3KdiFxVqo15x55rb2//aN4+3kIAAhCAQLgC/cxhPoLpu3GXN0g7fHegVhmVUh8bGhpq2YkYYTr29PTUbrDG76wa02FN+n/D7Hi9y1ox+MAJ9/PoV1iq/nR/vbta7foVC31pxeDwH7et66ppGK1qd8ytfIkr8wdA51Q6TfW/KaOUv/BSBw6Esf7MFEXRm/ZoPP4ecpzriNnDOllFpdjsMu9m5iuz4+P3UTpNWaLvmZlPkUTiX5momjfzY0S0LppOv5USiX/OplIbqrnmSxmK2UR0QZlz9oeZzR/woa4pY1+5v5QmNB0d+uevgCrlEpH9XouWSGReqCHivDYA6cMQGKPxcdcnebVSR9bzz5t0PP6E+Z7M30Splg55m9/XWrxnpbBmTS2gUQcEIDAhYGapLFu27FsicqkLySVdXV3XDQ8Pj7mkKzjNzH9rMVDzyI4dO/6jp6fnH4johQUFFO2IiPnd3NNgTW9vb5vjOK6zaojozm3btlX5SbSiDmEXAhCAAAQgAIEZL+B5Zo3vWTXM921bu8TzVOlGvUJ9g8OvI3I+S1L5qaNGbX8Dtqs9QnzHyo0jZ269cvHvGrB9oTdp5c27zxKiv84vWKLOH/P36/FeROb7uPlnbihnq9TeedG2tnez1s8nkW9UqY5DxSq1M5NMfn5ibLmwouecVOryaFvbbSLyeSZ6QeHpUPfMmjGfiCQSV5DI9U46fZuZlxhqDWUKi8Tj5mnHtjKncbg+Ap6fWhGt5+HJoPpcrBBr/ZXN/3vFfLTFTa8Qm1VQlNCBA9MeMBDmo1hq8pVV0JhW3VFaTw8116qdRb8gAIGGENBab2Zmt8GaeR0dHWuI6Iu2jV66dOmJInKhRfrNEzE5mDeLiFkLtuzGzMtNSLOdO3f+pmyiohPZbHY1M1ecOWSyiMimoqzYhQAEIAABCEAAAlUX8DRYs2Lwh2bB2Mv9tEo0fdZPvkbLs+rW3R06HbmJRP620drW7O0RoqNY05YVgz9cum3d2c81e38qtX/1pk2RsX3qU0WhvJwzH3/Fn7ZWyliDc5w/08eyPiaq5no1z2aTyQ9aNqWqybLJ5A+I6LRoImFC15kQET7GteyaODEgxPy1aFvbNcT87uz4+E67nP5TMfNq/7mRsxoCzPys53KVwswaz2gNl8F9vRpzI0nrozyHrWT+52wy+cmJHnd0tLdpncj1Pqv1G4n5I7l9l1cTrnHagjkscrRLPpz2IFBq9pKH7EgKAQhAwLPA+Pj4f3d0dJgZ824DGubvYevBGqXUO2x+dzaDRabRk4NGFQdrTHnMbMp9v21Hzewei7TPzZkzx8yuxwYBCECgKQV6enqGwmi4iPxq586d5nsWW2sIHBCR8wN05UCAvDMqaxBnT4M1TCaev5invr1u+2Y541/xmqnR0vfdNPznOsXfIJKXNlrbWqg9pyqK37Z606b+zWvWtOwa2QcfPelyZlpccN2Y9g0M8LQbXwVparPj9ofZtFZIdQdrptVX5wMHsqnU1dG2tm9OzrI5uartETmTRHZEE4nbI0TvTaVS1ZqhaEKgraxqX1C4ZwEt4nlmjRKZi3kNnqkbKwPzQ1YNYvYccoxFTHi1Q5+rsbFnknkVRRMJL4s0T5tVM1nUwrwi8TaYgKYDBx4PVgRyQwACEPAm4CEU2jnLli07bfv27Q+61dDb2xt1HKcgokCZPI/cc88995lzO3fuHO7p6TEzZtxCoV3a1dX1IdPuMmVOHe7p6TF/x3dPHSj/BiHQytvgDAQg0BwC54XRTGY+IoxyUEZjCAwNDZmIOKEM5DVGjxq3FTt37vTtbL0C8eqBvXEmudonwwc2X7t03Gfehsi2csPoGynCZsFsDNRU/4pcOL7vlPXVr6Y+Nbz60w8cxcxmZkbRxq7rExRlqNau58EamlmDNRPu2WRyh5NKnUZEN5R6urwKF+d1DtHPoonETQXrHIVUEUKghQQZcjHM7HmwRkTMLFhsTSwgRCYMmuvGIse4JipKoEXKr4Hi7Y+xkoMILHJUUZXY9S9gBsQw9urfDzkhAAGfArnZLW7ZxTLahOM4JtTusW7lEdFECLRcOmaemGWT2y/1ysxHd3R0XFTqXPEx2/YiBFqxHPYhAAEIQAACEKiVgPXMmrHO1JuJ6DgfDRvasnbRFyYCBvnIXO8sKwZ/mVC034Q9e2e92zKT6heSK1auH/7Z1qu6bmm1fsfS+pPENP3pBJHQ16uJJRJXCpHXKat/7sN8STSR2GObT4h+aNaAsU3fwOmS2VTq72Kx2NcpEjEDNzXZIvF4j5NO3xnmTTyEQKvJpfNeiYifMGhzyf+aIXdlUymrGx7eO9P6OWKx2OmilPV3YTkRxfxzm6mlwux5FgtHImXXQPG4ZlnJQR9h9hUGTYj6nVRqSzmTZj8ea2v7soi8yWM/ys1e8lgMkkMAAhDwJuAhFNolXV1d1w0PD49VqsGEHrNZY614kMgyFJpZX+YyIvpmpTb09va2OY7zlkppJs8hBJoFEpJAAAIQgAAEIFAdAevBGiK61kcTHtMUuYSYm/KpwJUbR05kvd/80tflo+/IElCAmQdXrh/+9darur4TsKiGyd63YfgCEjEDn9M2IXp42sGABzTRGUx0esBibLKb8IjW9SiRB21uRNpUHGtvP1u03mUTA9umPCa6IpNKmfWErLdMJjNM5l/zbgiB1qDXzu/MmgCLKYX1X7NBRavbLFHK80yXUi3KjI9brVlDRJ4HayJaP2HmvpfaFPN8m5tpJq8QlR5IMKHZfAwWKqWeaOUPn4h4DllHRI+Wuk44BgEIQKDaAh5Coc3r6OhYU2ntmqVLl54oIhdatHkqBFourW0oNGZe3t3d/cKdO3easGklt2w2u5qZbSIIIATapGAkEpk/NDTkeZZ3yQvQ5AeXLVs2ICIfavJuoPkQgAAEINAEAlZh0Po3jPYS0ake+3OQSV20bd3pjRLayVPzVw2OnKc0/QgDNZ7Ywk6smPnrqzbsfknYBdejvFW37u4g4c+UrVuk7B8XZfO4nGCiE1yS1OW0KBXWLKKEaP25sAZqiPnjXgdq6gIYcqUhhUBrykH5kClDL05r7fkPZMXsZ225ibazn5k8ofe6eQsU5uAhwJif8hBa0vPgUCqV2ldO2MysKXeu+Dgzlx6s8RGazZQdqRSerbjy5tz3/Nkoa9yc/UerIQCBJhMonuVSofl/W+EcKaXMLH+b50gKQqDlyrQJhWbKZ+aK0QTM7J5cmZVeEQKtkg7OQQACEIAABCBQbQGrwRoRucJjQ57WzBfcve4MM9jRdFvfhtF3aaL/EiLPf1g3XWcbv8HztKg7+j71Y+sbSI3aJZ2MmHVqXlCufaI49MEaInpeufrqeZxFHgmj/mhb2/VhrSPFzF/NJpOmvBm3hRQCzeaP8BlnG7TDzOw5DFqQNWs0c7lJF0G7MiPys9Y28fgrW2j9UOUEBWe9ztZIE9FzBSXk79g9cTyRg0XKhVPzPNvHFJhMJsuVl9/CZn7vOTxcxfWFmlkCbYcABJpCwIRCI6KnLRp7zrJly0qGA+7t7Y0y819blEHlBofKHS8uU0Qu7erqihUfN/s9PT1m3dnuUueKjiEEWhEIdiEAAQhAAAIQqK2Aaxi0izaMHOcIvda+WbxTsXrLlrWn/9Y+T2OkXD2wNz42P/UpErH6hbIxWj0jWvEiymY3rd606cLNa9bUNErKBTfu7fzutaeap5wDbSs3jCwhkasqFcKsfl3pvM9zftaZ8lmVfTYt8n8FqdvbnxfVekPBMfcdsy7Hee7JrFI8ISJzoonEt6xSN1AiZr4rk0ya2UV+N4RA8ytXg3zsY2YNEc312zQmOuA3L/JNPNfra6Ai346Jfpm/X+G9WfssXuF8qVOPlzo4dUxk+npqUycL32iRUjNr5hBRojCl1d44EVVc78CqlMZO5HVgjSoMiDV2T9E6CECgJQQ8hEIza8aYWStrizvuOE4/Edk8yDAtBFquLA+h0I7u6Ogw6+5NW7vGtI/Z6rkihEDLweMVAhCAQPUF9lK50MrB6jZ/01iH6Seie4ioGg8tmoe1TwzWldrm7u3tfYnjOC0R3ai2ct5qi0QiDw0NDZV9SNN1sMYRMov1FaQTotuY6AKiqUXSs0y0XTN9auuVZ9zejGvUXLzxvgVjOv1tyyduvF0FpA5DYPn4vpNvJKKKAx5hVJQrY+XNu89ilTJ1nps75ue1d+AHUSb6dyKqNJNNZj0RC3vNmo68/6N+ml61PErkj/mjblGRk4joNVWr0L1gcxNtlXuyxkshWgeawRiJx/uIqC1gzw4S0ayAZSB7CQGllOcwaETkOwwaEZmZF9h8CjDzcbZrvpSrQiwHaxKJxFH536Plyis4zlw2BNpkOutZrKVCdCUSiWM8t+lQbJw/FbSz9Xb8DKwRK1V5cK31nNAjCECgwQTMrBZmvtSiWZd0dXVdNzw8XDDwbkKPWf5cLBkCLVevCYUmItfl9su9ioi5d1EwWNPb29vmOM5byuXJP44QaPkaeA8BCECg6gJ/v2PHDnMfNtStu7u7l5l/YFtoJBLpr8b6XM241pXW+g1EhPW5bD88PtNprT9MRAPlsle6eUwDA6KIqXCWidD3t65b/IYtaxd1aoo8TxS9oOOpxKy71y3+i61rF3+zGQdq+tePnpLWsXuJxGZqdDlLHK+ygBCtW7l+tGIs4rCa0L9h9CpWakcYT/p2LJj3HhI6w6Vtj2weODXUm6SJRKIhQ6AZh0wsVhAGTcIIHeQC3KqnWSm3m68Vu66UurhiAruT7XbJkMqrQCoa9R4GLchgDXPBTRav7Z3p6UUk8MwaISr7hE2+r6OU97pE3G7+2w/WaD1tgMVRyvPsEdMnYW7pEGhmYC3/2tm+1yWMbfMiHQQgAIEwBDyEQpvX0dGxJr/OpUuXnigiF+YfK/feLdSZ2/lcucy8vLu7+4W5ffOazWZXE5HNzzeEQMuHw3sIQAACEIAABOoiUDBjprgF93eOvpKEjs8/LhH+xMQ+s2wj+kP+uWZ8v2r97m7NYkZyFzRj+2dam5nlU/0bR/befeXie6vR94s+/tAcp33s8yLyelM+E/00SD1mIFBEbEalfxaknlJ5HebjSRpyzfcsjY0V3Jhj01ZsvgSkOKSct1LaRcSEpwi6PcrVmTZcsl1CdIJZj7zkST8HRZ5k5sYM/3XwoOeZNcxsQgT6kSDS2oSjwuZfwCbUS8XSI0S/tJmdIo5ztGVIl6n6uPJgjQmJWPH3wqmCDg26P06ZTP4hyo6PPxiLxRYVHLTYUUodqEbcAYuqa5IklUo94sclm8n8qiYNRCUQgAAEygh4CYVGRCYU2hdzRSmlzEN2NrHHyoZAy5VlGwrN1MfMpt735/Ka2T259y6vCIHmAoTTEIAABCAAAQhUX6DyH+XCbyU+fMNHiH689cpF369+s2pTw8rBkb/Sh36h9BrzvTYNRC2lBGKi6fYLbtq9+LvXLHm0VAK/x1Zu2H2aI2O3E9HJU2Uw+R5EWb1pU2RsH33eKsSUcKBBoan25r0RouNt/jrKy1Krt2YmiC6q7JiifexaCqgAgzWReHxlCOHLdmZTqR7L5oaSLJpImNkfoc3mEeZLs6nUnaE0rhEKEfG/Zg1zqhG60MRt8DWDIr+/6XTaas0axbzw8G9o+SWUf19xBkt7+3zSxV/N5cuisbFSa9YcyGQyeyrkmqmnxuEyUy89+g2B5hfwEArtnGXLlp22ffv2B3t7e6OO4xRG6ChPUTEEWi6bh1Bol3Z1dX3IDDT19PS81DbMOUKg5aQPvzqO89Hu7m78bmhmAYucfVimMd/19vaenM1mr2zM1qFVRoCZ/7hjx45DD8BXmURE1pergpnN5/mscudxHAIQqK9A2cGaiRkGPPa6/OaxyC35+838vm9w+GoiuqmZ+zCD235MLKJuXz2w97ywQoetHBx9G4t8unhghcX/YM3Bfadcy7ah9Vh+Evb1ZK1PILuFNMOuunJ5ItNm5JmZNZbxrCuXPQPPpmOxxyjtL4KeUmp1UHcmuq3G7GaQJrSBGtN2VuqpGvehmtWZtarK/mx3rZjZrD9UuM2adUy0WRcZFIkzkblR42vTIr9jpZ42mbPJ5G4iqjQDy4SW9R6aLK9lTPR7IrKa3TQRcs3rd3yFmTVxx5mv7ct7Dusb5V04vIUABCDQwgImFFpHR4f5WegaSkxEzCyWtY7jmJnbVrNNbUOcTQ4aua5bw8xHd3R0XGTWrjHtsZyFihBopT/Dl1v6lc6NozUVyGazJzBzzdb4rWnnWqeyB4ioJoM1O3fuNPc8S26Ta6lgsKakDg5CoP4CZW/oZNvGXstE5qZPbhvTnPl6bqeZX/sHR/5JiP6+mfsw09suRGePdSY3Tk63982x+sZd7Qcj7bcwydtLFZL1GQZt1YbdL9Ei/1SqzFLHROu9pY4HOSbMJzTkzBrmaYM1ImL1x1wQjxbNm6WDB6etG2HZ1zBCoOlMLLaJUjV84K69vdPT0/8WGMpxnrRI1hxJZs2aS9lAAaUK41qZkZ9s9s21+qOiGsheZ5/kt2HiBkUupFx7+4k0Pl5+sGbWrIWUzQb62hUi67BXwnyM18pYqbLfF1qpI2zD5wlR2XLy/fAeAhCAAASaX8BjKLRLurq6rjOhxywfCHINgZYT9BAKzcyCuKy3t3eL4zhvyeV3eUUINBcgnIYABCAAAQhAoDYCZQdrFPEaofxbHLJp27qzzZOUTbtNhKV67JRPTT7x07T9QMNzAvw3feuHd2+5quvfcke8vJr1ZA6yfINJXl4m31Pb1i12W4x5WtbegR9Etaj/IKLEtJNlDsyKtYc+WMMivyPmO8pUWfIwEy0WoueVPFn+oLlT/53ypwvPMHOpUIoYrClkst0za//kf1Hb5qOQQqD9Dx04UNObtnHH6fTw9L+VRzoWe8rv7CSrCmqYKJHNzrVZ76Rck7TW03/OMy+wvYlfrtwWOJ6l8fE/VupHPJM5KuhnU4geqlRH/rmJMGi5gaT8ExXea5GC9cLyk4rW822fnmWRUiHQ8ovDewhAAAIQaCEBD6HQ5rW3t/+diFxo2X2rEGi5smxDoTHz8mw2awaNXGcDmbIRAi0njFcIQAACEIAABOotUHKwZvUte2ePOalX5TdOiXwuf7/Z3q8e2Bsf25f6CtGhheObrf1obxkB5o39G0cevPvKxfeWSVHycP/gyOuF9OeZeE7JBBMHxUxR9bzN6pz3D0R0poeMv9t8xanln9b2UFB+0mw6/a/5+zbvo4nEXeR9sObhbCr1WpvyK6TBYE0FnLKnmCvePC6bj4hCCYHGXPPZllqphaEPHBw82DIza7TWc0mZaFy+t2ljPSKywOsMDt+1N2hGIXqEiKbZ5DdXMwf+HlNEv6hYSV6FE2HQ8vZt3iqtnyhXvlKq0/IpaBNw22qwJppImLXlsCaZzcUh+lM2lTraLilSQQACEKitgJdQaMz8IRNl1qaFtiHQcmXZhkI7tDTERDtyWSu9IgRaJR2cgwAEIAABCECgpgIlB2vGdbKPiKdmBZibFHet67qHmjT6pRmoOdiZ+gYTraqpLiqrhUBMNN1+wU27F3/3miXmplDFbeKzMD/5r0Lm0+zyN4Qoz4sk928cOUc0faBiI6adDH+9mmlV2B4Q6fS8zo3IxHoOtlWUSBcnopESx3OHzPfUK4jIpPO7mdkCZvCt9OrZzO0k4mWArbAdzE+TyI8LD9Zkz9MgZV6LwgiBls4kk7fnlVmTt6L1Atun/y0btN8sR2KZtuGTSSQyN8hgFiv1bHEnssW9dgAAIABJREFUmWhB8bGZts9ED7v12QyeBP1saqJfutWTd97zIEgmGt1HmWmR7iaKFBGrp49NYiEqO0Mnr33m7Yz/7BR5VNptmUHjSp3EOQhAoDkFPIZCc/kja8rAOgRaLoeXUGi2A0ZEhBBoOWC8QgACEIAABCBQd4GSgzVCXPyU/GZi9hVqp949xEBNva9ATeo/JhZRt68e2Hve5oFTy660vmr97uePc+o2Jj7bplVCMmqTLpdmckbal4gokjtm88pCZtHqxtgsQwUUNJY56OLs6Wwq1VtQZt5OJB7/AjOfm3fI01uzBoQTiy2lAwfKhrSLtbefLSJ+Bz7MsN/3MqnUGzw1rI6JQwqB9j0iCjpQ51lBMXeG+cNIiMp+Ljw3rgEyiNbzAg4YlJp4cVQDdK2uTRAR18EaZj4uaCOjRD8vdQHKlHtkmePlD4+Pl/+8M1uvWcN2M2vMzNVY+cbgTJFA+WtTlBC7EIAABOoh4CEUmm3zPIVAyxVqGwotl97tFSHQ3IRwHgIQgAAEIACBWgpMG6wZGBB1v4y+uqARmjyte1GQt447KwZ/mThI+zdjRk0dL0KNqhais8c6U4NEdHmpKleuH75QM3/Zy1O+kYiqNNtjWjVjTmo9EZ007YTrAfUj1yS1S2D9ZHWuSWxmlVRpiyYSJhzj2wIU/0SU6EKnwkCNKVtr3Wn7CGCptmiRoANWpYqt2rEwQqCJyFer1sAKBYuf2V8VyuPgg40VSq/9KaXUPOtQViWax45jZhoVbzN+doTNzBoiWlgM53E/k0qlfmeZx8S68zpYc5CIkuXKNzNrrL8HLdasSSQSR3kYeCrXrJl0HIM1M+lqo68QaEIBL6HQbLrnNQRarkwPodByWSq9IgRaJR2cgwAEIFBFAWae1dvbe0TYVWSz2dleykyn0/N6e8s+P+ylqIK0Wuu2ggPYgYClwLTBmvvnjywi4s68/M+NPfPsrrz9pni76tbdHTr13N1EfH5TNBiNDEPgsr71o/duuWrRf+QKW71pU2R838kDQhOhyazvQ5kbWvufePrnuXLcXvsHR98kJJe6pSt13mG5v9TxOh3L/79v1QSdFwYt2t6+lEQKB3uLShGtH3LSaZu1TmYJ0b95uWhFVY2z1n2pTObXRcen7zJ3Bgod1Vw3/MMIgZZ00mmzvlHtN7PYfZhbkw20uXZdZJ5rmgoJmLnU7MRwzSvU36inRCn3mTUixwoH+MYiMt9VdiH5Zs1aSNmsp8qEqGKoUMU833agT5j/5HattNYLAq6f5FZFS50XIoRBa6kris5AoPUEPIZCcwPwHAItV6DHUGi5bOVeEQKtnAyOQwACEKiygIh82XHCf7zLa6SJSCTycDXaUWW+uhcvIj+JRqM9dW9IgzTAcZy7ich3VKD8bkwbrCHm5fkJhOR/hgbOt7t5kJ+xju9N6LOxZOrbxISBmjpeh7pUzfKZ/sGRPXevW/zARTc/ePT4vsxXheiVPtryY9vPff/60VOE5DM+6jBZfrtt3eKqPU0bTSQuJCLzr+yWTaX+gYjM0/QdftaFKZiZILKSRNzW7Pk8EbkO1kQTiY8Q0QvKNrzyCS1E/y+byVjNWlIiwUJrNdEN/0giYb7jZ1Xmq3yWmc1sywOVU1XnrJlZ4/WXr0otYeaWukEqInM9rzuVB6SUGsvbzb2d8YM1NjNrhDlouLhf5MDdXuOZzJHa48AQu8yG8bJmDYm4/tzSSi3wNJrk1ukWP99q30UtfrnQPQjMWIEQQ6H5CoGWgw8rFBpCoOVE8QoBCEAAAhDwJsDMztDQ0DPecrVu6p6entDGTqYP1hAVDNYo4R3NRGlmUoztS20iIhM+CdvME2gTom+u3Dh8taMz/0ZEx/okGLbJZ0LtET13GxF7mmaZK1uIrAYTcum9vjLzm0XkTRXymS+Td0+cb2/vJK0rJC19ikWmbnaLiOvNOZu1DibWkNF6beka3Y8y0RXZVMp65ocwHxlkZo3Yrd/g3vAapFAiawI+/W/Cxpnv2LpszBw01FRBu5sthF1B40vsZNPpfyIi88/XVuK3CzPbztM6XL4qbvBMWWbXmTVEdEzAbvzSNr9W6hjP31lus2FE5lsO9Gml9f+5PgNnZsFJmCtM2eo0abq8n6VN2gM0GwIQmAECYYVC8xsCLUccUig0hEDLgeIVAhCAAAQgAIGGESgYrJlYr4ZGziKzXPbkpkXfk3vf8K8iPDa454vE8pqGb2tzNvAxItpjQoQJ0URcSUUyV4jNDSq/gyLVkDiJNVvfqC/VACa2+tyz7L9ZmBeVKsPmmJLqDtaIyOmV2iFEjxDRxD23uOPM9/qktilb561ZM7H4u9vNOfcbUgnR+rNEZNZk8L4xfzSTTHqa6TQxW8N7TYdzNM/MmoQwX3S44b7ePeek01t85QwjU/hr1kwNNobRvFYrI5FIHOl6U77VOj29P1kaH//j9MPTjhw97YiHA8xsHXpTtF7odYaZEJmf4eU35krxoseJ6HvM/O1MLHY37d//RPmCDp1hkaAzjdyqaKnzwlz5+rRUb9EZCECgWQVCCoXmOwRazi2kUGgzLgSa1vqZSCTyvzlHvFZHQER+VZ2SK5da5ev7islIHJUbcejs700EEZuEMy1NvT4bM80Z/YVAswsUDNYMLxh+EYmak9cpZ9Yz7aN5+w39tm/DnhuJ5c0N3cjmbtxvtqxbXDKk1qEZJvtPUkIvF+JFrOg8EjE/0P3dcK+zkzjZe92asHJw9G1McrlbukrnHcX3VTof8FyciF5SqYz80D5aKX/rtuQNVEws/l6pQiJipSre5Iu2tV1PIqe6FFPyNIt8KZNKuYVhm5bXapBpWq7DB1ippw7vNe67SCJh1hOaG6SFLPJtIkoFKSNQ3pDXrHELDRWorS2Q2VFqgZ8Zdy3Q9akuCNEfcoPaUwenvzE/6wLN+hIi6zBoinmh1zkrFrMa5xd163EhupOI7nRSqe8TkRmwIUomi5KV2Q04Y7FMqa172P1BhtbtO3oGAQg0lUAIodAChUDLYQUNhTYTQ6Dt2rXLPHgZ/irauYuC17oKVOv6rlixInHgwIGnPXTuAzt27Piyh/RICgEIQAACeQIFgzUi6sy8c8Qkv9o8cGqpxYbzkzXE+/4Nw+8VkasbojGt24jFZj2gUp+JbetOMTdvfzr5b2I9kuW37p7XluYLRfiviGiFn/VQ6kHJRH+6+5pX/KZS3as27l6stXy6UhqLc6nx2c9YhVuzKGtaklgs9lIhKvg/XpxIRKZC+4jWC7w+qW3KY6Xyf3FzXdtCi5RdmDoej79Mi7y/uJ2W+78Q5gdiicRVlumnkonI4qkdP29E+mOJRMH3p59ivOTJpFIbLG4gFxQZRgg0Yf5aQaG13zFhuULbNG6QVrSc+F6omKL1TzLR71x7OXv2kZTJBHo4IauU9WCNMHsOg8Yi+1z6YQZrTBvuIKXuyI6Pm4cWvMfGnKzEJiymS3tm1Gml9ZOYxTajLjk6C4GmFQgaCi1oCLQcXMBQaAiBloPEKwRcBMbGxpYSUbtLsqnTkUhkaGoHbyAAAQhAwLNAwY1cLbI4/2atsDI33xt+W7lh9I0i8vGGb2jzNzBx8IhxE/LLajbIf1225Fkiuo1ENvUPjr5SiK4jpm4vP+jrQSZEFWfVXHDj3k6tU7cTUVvA9u0eevv5lo8oe69JRyKns0tIsvyZNUqp+eKSvlQrlOPkD9a4PlnOSpULOxXRSn2ORGKl6rE49iIiusHr0+YW5bonEbm+xvWaz83N7g0rSBFGCLQnsqnUfxeUWvudUAdrmLkpZkXVnvlQjRMzOHx8L9SrvdWol/MGtcuVH0+nF/oJI5lX3gEaG3s0b7/iWxE58nDA2opJp05qkcendkq8USJnpNPph0qc8nWIiVwH730V3KKZVPmfjS3aY3QLAhBoVoGAodACh0DLuQUMhTbjQqDl3PAKAa8CWuuCda1d8v96aGjIzErHBgEIQAACPgUKBmtY8SmUf8dRpOLsAp91hpqtb3C4h0S+GGqhKKysgOLIK20Ha0wh/RtHzpENo4PCtKRsoY12QnhnuSaZmUVj0dQ3iejEcmmsjzNX9YkTFnm5W1tEqcMza8xaID62dCz2FKWnJuC5lhHR+okSi5hTLJFYJyI1nZ3io7sNkUWIrG/qTjV4zpzZnMl4nnU0lZ/I/Hgwaxxl8o/V+L1ZUyPUxe5ZawzWVLqIjrOHlbqmUpJGPifMHySR4vBenpqc/z1ZLqNmPq7cOcvj1rNqTHlM5Hk9GLcwaBYDNbF4PP7idDr9E8s+uQ7eW5YzI5KlUqmys05nBAA6CQEINJVAgFBooYRAy2H5DYU2E0OgGbPe3t6XaK3fkPPz8qq1/t3OnTu/4CUP0raMwKtseyIiVb3HYdsOpIMABCDQzAIFgzUk9OL8zjCXD1eUn65e7/vXj54iNLF+gt8n8evV9KatV1jMmhcftelA/4aRy0XTLc22bo2o8r9gjHWmTOizcOL8Vv8XmdPcrlP+zBpink9+nqA/eDA3syZhs+hgKpWatmZNW1vbn2VFPuLWXpw/JMAi3hei3r//yQxRUw9sV2OxezzNXvl/VSaTMevWNc3adcW9iba1fbD4mNf9gu/JMpmzkchPItnsxWVOux5WkYhbiLLCMkSOJvY2t0aJeB/kJWqPxOMrFNHFwnyRMH+XiNYUNqbs3pFlz+BEsYB54mF/8UHsQwACEGhUAb+h0MIKgZZz8RkKbcaGQNNav1REPpTz8/KqlLqLiDBY4wWtBdJ2d3ebh566bLvCVX4g1bYdSAcBCECgmQWmBmu6bt0doxS9oKgzFUNmFKWt6e6KwR/OFRKz8K3rk/w1bVjrV3bu6lv2zt58xakHKnV15frhNSIUdE2XSlVU69zTZz65aGRridL7BkeuI6JLS5zycyjZkU3e4yejhzynu6XNMufPrJnv7dbfROkHiejQtJqOjgXkuEbcN5NqcoM7ueZxVuTfGz08Xq6xDfHK7O3GbkM0OngjtNadpAItCzKtEalUqlxYvmlpcaAJBUTmBm21EE19T5Yta2zsUYfo22XPu5xw/eYszs/seSAkHYs9kTcLsrjE/P15kXi8n5lfN7neXHtu0rVbKLX8QkTkh8z8y/xjeF9agEWeKX0GRyEAAQg0poDPUGihhUDLqfgMhTaTQ6D5nm0sIvGcO15njoBS6nwRsf4DDOvVzJzPBnoKAQhUT2BqsOb4tFroFIWX0cJVW08jSJdWb9oUGXss/jUSekmQcpDXl0DsoE5dQEQmFFjJzQykMfGnSp5s/IPbBwZ42oLKfRtGV5OI1Ywiqy4K7dh87dJxq7R+Es2adTRls25hcrI0Pv7HXPGKudPHmjVTAy/xbLbTYs2GaTfGY21tbxeRv8i1A6/uAkI0IwdrRKmwB+fNPXLcJHX/yDVrCrMQauCweVGih0uFbqwzyjGe6z94sPwDOLNnHxXLZi8SkdcT0flEVPKGDHuYneOk03/tuY3IAAEIQKBQYFbhLvYaScBHKLRQQ6DlLLyGQpupIdCMl4gEWU8u6HqtuUuG1yYSEBGsV9NE1wtNhQAEWkNgarAmS3oBU+GAeYS5ejeTA/iN7zvJ3DRfGaAIZA0goDT9VaXBGub4u0iac2FhIfqfYpq+DcMXkMhXDi0TUHzW5z6TCSVTtS2azbrOqplcf2TqgW7xt67D1HofWqkFFmHUCgdrZs06RrLZG6sG0aIFs8jMHKwRWcAeQz+5fASmPr8u6XC6GQVmzZpL2cDDLE4ymWy0RVJNyMk5Hi+JCT859X1fkHf27IXRTOZRoaJfAgsSHdph5vIDPiXS4xAEIACBgAJTf6sGLAfZqyCgtf5lJOLpmYhqzbb0VG40GvWUvgp0dStSRJ4f4HfpRT09PViPxN/V+8aOHTs2+sta91xYr6bul6C5GiAi5sGvum7MfAYR3WTbCBFZRUQVowfZluU3nYjUtX6f7T4ZPxcK5MznLpRt6hdgpdVRUhQDyRExT6U21NY/OPIWIfq7hmrUDGuMMPVVCoXGQn/ZrCTsOHfnt71v/ehSEvkWEYW6LpKw/l5+PVV4/3K3Mqetw8DcaTHYUlzs1M1u0fpIi1/+CxZQjjrO5TQZYkiI5qjJp+CFyCxM3VFcGfYPCfAMDYM2Mfsr3A9B4eBhuGWjtDoLJLLZOaVHJ+wbxkRmoCbwiI99jRYp29sXkp42AdQtY9lBlng6fbRmLnxap0xpeoYOFJfhwGEIQAACM1ogGo2+1uOs/NcS0WfCRhMRU671prU26T9mnaGFEjLziQG6Y0LLnhcg/4zNKiJ7mrHzS5cuNZ+Xk23bjvVqbKVaO93OnTvrPqjb3d1NFvempi5ENBrdOTQ0hIgbUyLWb8wMaPxcsOayTzg1WMOK5xT/sqWEjrUvqvopV2wYPVcOrW1R/cpQQyWBtoM6fRERfbU40cCAqPtpdFHxcY/7e4noVI95wkj+iy3XvOI3uYL6B0dOF5JtVVhL5Xdb1y55MFdPNV5Z5HRxmYEgIgXrMJiZNUXjtTZNmxqsUUotKP4OKVGAebp7assmkwNEZP5NbLkbq9F4fBcxn5M7jtdCgZl6w1TMOh2SWz2j0MTXnsjU59dXfmRqaIFUKvWrohmRZtC9OKSOamtrm7aujeM4R5jOKaUaboZxLJs9Rryv3VQwUJ5/4bRSx9j+v+JIpGw5+WXiPQQgAAEItL6AiKz22Mu/OOecczrvvffe0H7/Wr58+bxUKvVqL+2YbPeMHKwhoiCDNV6YkbYFBKLR6HKLv++neor1aqYo8AYCEIBAIIGpwZpSpWjio0sdr8exlRv3vIi1vqNcHPV6tGkm16lETCz6aYM1w7OHO4mUp/nwxY4i8mlmfh8RnVB8rrr7vDVX/sqbd58lRGb2y7SbeLk0vl+Z7vSd1zKjMHueWcNEntcDEaKpNWvELP7uNkBEVDBYU647wrzQx8BRueJa7riKRB7LDWy1XOcqdMjE2Q71c8Ec2s2CCs3GqcYRyJRaoyiZTDbV50CUOtIrKTM/Vi6PaL3Q9smziNZ/KjnNqKPj2Eg2e1a5OnDcm4BjHlg4cAADY97YkBoCEKihQHd39/OJyOv3fjQWi11MRJ8Lq6nJZPIiZi65zlqFOhYvXbr0pF27dv26QpqWO9Xb2xt1HOdFLdcxdKhqAlivpmq0KBgCEIBARYGKgzXMYj3lsWItAU9edPODRzs68x2i5lwHJWD3GzK7EL3ywpsfePF3rj795/kNzMbn7Ve0P/+Q5/es+BESeSMRm+mTVqFZPFdSMoO+3RzuW7/nfGL97aoM1JgKpOqDNebp8ZeW7GLeQVEqf2aNcZ54kjwvietbJjp8k9OEUXPZmNkq7BRTY83qc+lWzU9nPCzyXfPGVbFCxWwze8u6BSJSNjSUdSFICIEaCwjzUexxhpkWKTtQrpgX2s5XS6VSj5bqbiSbfSUzf7nUORzzLhBznHMyRBis8U6HHBCAQI0ElFKrvTxxn2vW5KyW0AZrmHlNrmwvr9Fo1MwKmlGzaxzHMX8fmnXvsEHARsA8I7fcJqFJIyJ1D31l21akgwAEINDoAlM3wjXpUqE+ltS7A8tv3T3PURkz4+HP6t0W1F8oEFHONYVHiLatOyU1uXB98Sn7fR35zZZ1XTtIeL19psApH33FU4vvWTk48lfE+rtVG6ghem5fQv9v4NZWKCAWi5lfxCsOxJrsBWvWzJkzv0KR5U+JHJ5ZI7KgfMJDZ1jE5uaTWSurOFSRW9Ez63wyWfYp+VaGEBHXAUEv/WfMrPHChbQNIsAinmc9s0jZ7wxh61nU5vfEsVIMzHxMqeM45k9AaV12cM1ficgFAQhAIFwBHyHQcg2YCIWW2wnyakKgEZGnEGi5+gK0P1dE070yc9BQ5U3XZzTYv8DSpUtPJyLr2dxYr8a/NXJCAAIQKBaYuqGrWB7XMi3AzPNXbXjgz+5ae/pvizPWYv/Vn3hgVizlmFBUi2tRH+rwLPC2C27a/eHvXrOk4ElbJjKDa5d5Lu1Qht9tuer0n5i3HdH4B8d0ag0JHe+zLPtsTN/40YLRf2ah6+0zeU/JRHcMX7bEhOKp2qYjkZfbPHWdZZ6aWZNIp+f7CauVf7ObmV0Hayo93T0F0tZ2lO36CVN5iL7LzF/P27d+KyJvIaLzrTNMT3gTM/94+mH3IyLy+aI1NdwzEZmF75I2CXNpEonESVmR03L7zfoqRC+c9lMqQGfMTe9IPO5pUdoA1QXKqkR+n8lkRsoVEo/HT3OITip3HsebQ8BJp82sTrdtoVuC4vPMXHagXESswk4KUcHP+oI6mBf6+N4uKAI7hwXKzWA6nALvIAABCNRPwGcItFyDQwuF5jMEWq4dMzEUGu6p5K4+Xl0FsF6NKxESQAACEKiawNRgjaSjj9H/b+9+4OSqyvvxP8+Z2d1kkyCE8CfZNbUW1EqVwMZiwsxmEahCQKs10e9XC2gtsT8hKNbCt3++pVaraatCqH6FighaK8T6hxBjJcFxd0lE2QRQKFWgGneTIJKICZudnbnn+b3OZu5mdnZm7jl37vz/zOuV18zce+75876T2d373POcuJ7VkBbvLUT0iVk7qrzh0lse6tbp7GYi/v0qN4Xqwwt0xWPqb4novflVKKVu1lpfGeIiNAnL9GyaTe874/Dqjbv+b5R5jfP7OeO10BomqvqdwVpk1jo/M/oRwRsWMXfBBD2ydOTImF9Im/Vm3BesJp03s8bmzhubNGgdnneK8+LZIqlMOv0Ffzwuzx1z5lwUJo2D3wYrdXfmyJHv++8dnufHu7pudyjvFy15h7xfoPDZE3k7M3+kcHu7vxfmdzLRO5vBQTN/loj+rFRfheiDzHx5qf3Y3jQCgfFIFjlZAtYHKxxtuUA5E51cWL7Y+3IzI13WvSlWN7bNEDDB+BdmbMEbCEAAAg0kEDYFmj+EqFKhhU2B5vej3VKhiYjrGkM+FZ7bUEBELnQY9lOpVGrUoXzDFR0YGHiF53mvsOkYM/9mcHDwfpuy7VgmmUzW/WZIZv49l2s8WuvVyWSyrr9/K6We/973vvfddvzMYMyzBaaDNXN7f7J/fP9p5g/EOQXF3kMinyRm25TmBYe7vzWpz3Q6di+RJNyPxhE1FnjPRRt3bdy6/uzH/XY3X7XssUs27v6MkLzP32b5/Pi85+Z8Or9s96lP3jG+/7Triej0/O1VeF31QA0RHXxmjmyvQt8Lq3x14YbC97lUddOTaUSpUGnQWKlja9YQBaaoYovULlopq7u888fESu3Pf+/yutLUWkrrfAPrpru6uhZPnwDro6YKuo+V2XoKu1tXULpWAoGBTqU6MLOhVmejau08b1OzQ9qy6eo4Fis9K8akVbMJ/pSZnYM0aNPUFb9grFVTsSEqgAAEqisQQQqxqVRoO3fuDPU7tBmdSYGWTqdDpUDzdXLjaIt1a84555zjiKjuKe59ezw3tsBFF13Udfjw4aRtL1thvRrP85YR0b/bjFlEJgYGBk5IpVJO2S5s6m6RMl+v9zhcAjWmryJS97U3tdaPEJH5HOIBgWOLt29au9ZcN5y+4J5n84qLNz78xrz3VX150cZdJ3Wl1XcQqKkqc5SVxxTz59fcfXcsv9K5BzqvJSL7wATTWCwmb9p0wxmT+fWYzyUzfTJ/W7O+ZqL/qHYKtJxN4MyaGevVHP3hFBhoKebOnje9Zg0RBaZBy8TjJVPx+PUr5sX+a9tnEXEPYByrPNTY/cPTnZ3P+a9dnj2lQgVQmNl5rCwSqi2X8aBsdQVYpOznTESwzlN1T0Etap/x869kgyGCr7EygXKxrE+ISn/3WNZRckzYMS0gzM6zJ6cPxgsIQAACVRaoMAWa3zs/FZr/3vnZpEAjok7nA2ceMJUKbeam1nzX1dU1QEQz/l5vzZFiVFEIjI+PryQis46s1aMV1quJxWIpq8EeLTRHRKyDWQ71oigEIACBKQE1w0Fo94z3uTes5GNrbnis0l+GilU9Y9vF//LwyxTRA0SE1GczZBr8jcg54/tPvy6/lybo0n2g62IivpGIyk4gYKL7ldYr73lf35P5dfivuVPfSUS/8d836zOLvqPqfZ83zyw8HZjSRkSm16sxfVLMoWbWxGKx/GBNcNDjyJHARZNNOh1XJ9a69EXEgMrYIshUtopDh0LdFRhmnKYfUmah8FL9FIv1hEodi+2NIaCZnw3oCYI1AUCNvpuJxq36KOI8EzSdTpcMlDOR+bkR+Ci37o1Z/ymwAhSwExAJ/DlpVxFKQQACEIhewKRAi6LWSmfnVJoCzR9DLhWa/7Zln0Xk0pYdHAYWuYDW+gKXSh0DHS5V16xsKpUy1xP+27ZBrXVFM/ts20E5CECgPQWm06CZ4bOS+0T4T2ZRCP3ukYXpvyEi868qj4tv3NXPWpvpcsEXfKvSA1RamYD8/eqNux/Zsv6sLX49uVkyH3jDjY98Nqa8PyWiNxDRS4nIfO72kfAgKf2le6/u+0//mGLPm9ctH1+9ceQuIjZ1NOvjp5vX9z1A11S3+/FsNnBWjelB0Zk1NmlwCro/MTHh3+2/IHdeC0rMeHuEiMy/8g/mwGBTYQWZzs79lMkUbrZ6L5UEa5hNoCZUikjFfIrr9NypAYmUTmdUasQmWCOhulmqRmyvtUDAzBoi6qh1l9BetAJCdNiyRteAtvlyzA+s5zdjUt+a7+/AB5eZwSgWNwkENoACUwIVzhSFIgQgAIGqClQaZMnrXOhUaFGkQPP70Sap0JQJ1nCIv/VEjq0n65s5Pi8OEVibFJH/59jOVHFmNjcvvcf1WGa+VWsd/HdqXsVKqbeKSE/eplZ62Vbr1fgnzqRzY+aX++8Dnk2w5kMBZbAbAk0noLVOqRDrWddyoCLyEiKyXq+XmTcQUUOlLTTO5cxmBGs6OLttUjq0udG+8CAh+suLbxp54FtMhPAxAAAgAElEQVTX9H27cF9F70V49caHP0gsH7O42FtRUzi4qgKKSDZdctOuS++95uwZ6c++/f4zzR0Kf57759yJi/9l5BISdX5zX2zmL9Ro3afA9WrMCRClZsysoXAza8x3xdQaC3PmzDkpGxAMYKKgmQFTnw12D2JoeuGFkneNB3zgzAXu+QFlSu4WkVCzakyFUzNrQvzRxEo5p8gRkRMDVy0vOUrsaAQBpfVzZacoEh3fCP1EHyoSsEmDZr6vuhxbKT1TY+7cRaTNV3nwQ4uU+g43F0asU2UEt9TeJTh4Fl17A2H0EIBA3QQiSoHm999PhXabv8H22aRAY+aosn5MpULbsWPHU7btN1u5/v7+AQk3A3bP8PDw+ysZbzKZfC8RrXWs41th200mk68PEaz52eDg4DrHPlIymTRrS7RcsCaRSJiMG322Hq2wXo0/1lw6N9vPwqvPP//8U7Zv3+78t7nfHp4h0IgCw8PDJohQNpBQ734nEokBZrYO1iilPp5KpX5d7367tD8jKPP1q855joW/VaICxcx3XbJxl9Wd+yXqmLH5jTf+6JRLNj58D7H8EwI1M2ia9c1cYdp68cZd62+4QWZ8tlwHNHDDd+Orb971xtU37/4+a95MImZGTrM+PE3KpHKr+oNFrP5/Fp1Z49o7kek7tT3PC1yvRiwvQImI613jJlBjd7WxcIzz5lU0k4+PzqwprNXufYgZRKZiCTGzholcTe3GgFI1E1BK+bPYSrUZ1UWLUvVje/UFAtN9dnV1Oa/pRUQl/4jsyGZt6rtfRN7mTU5+oxjBnDlzkAKtGEz4baWCYuFrxJEQgAAEIhCIKgWa35Wws3RCzNTwmyz63Oqp0ETksqIDD974g+AigSXMWjlOD2b+otMBeYVFJJH31vblvbYF26GcUuq8Yjdvlxp7K6xX44/NNZ1bOp1GKjQfD88QgECkArMvqLO+tUwLxwnRtotvfOicMmWCd5nZNDfv+hNPZZ4QlkuCD0CJJhLoYKKbfnji7pFLNu667KKNu6wvEl96y0PdqzfuumD1xt2fmrfwRaMk9E0Sqeyz1gBwQrJ56/ozR2vRFWG2mlmTZZ4xs4aZ3YMWeYEKUSr4ePs8/K7rMYRer6YzkwkMMpU9bxXMrOGQwRrWuuSF1xJ9NbOHjiuxD5ubRKDcmiNmCEzU3SRDQTdLCwROzfaUWlT68JJ7Ss481KXqO5p2759iRKdn0+nzvcnJu4mo6MwfL+R3WcnetvkOYQ79M63N6TB8CECgygJhgytlujWVCq3M/lm7TAo0Ior0AmkVxjWr3/XacM4555i/Ad4asv37Qx43fZiIuAZrfj1v3rzptOrTFVm+YGbnYI2IhG7PsltNVUxE2m69Gv8Eua5bw8wu6eL8ZvAMAQhAIFBgRho0U3r5gbO3/PDE3Q+TkJnWWeyxiJVKrb5p5Jot68/+V9fUThffNPIGvnn33xHR7xerHNsiFzBTun8n8lqDKhRaJkR3mGjg6o27fspCjwrTk0SyX0jlpp/prqkL1kIvYaJX6vTUdNuOkEuABPWobvtZYhtr1Li5KP9Ki7aydOTIWEG54GBLwQHEPD2zRkQWBuVBZuagmQF+C65r1oS+sKVjsYW2KYD8zuU/VzKzRkTCXHSlTEeH2/o8ZvZQNpvfbbxuPgGz5sihct0WkfkUIq1euTqxr+YCgcEa8byTg75rC3vNzKXToDGfVJBi9Hsicqs3OfkfRJS2+ebQWi9CmsVC9fDvuXS6ufCV4kgIQAACFQo4pkD7LyL6XYsmnVOhOaZAs+1Hy6ZC6+zsNOsRm3Slzg+t9TedD8o7IJFI9Jn01nmbAl8y891bt25NBxYsUmBgYGC+53kri+wqt+mFeDze0Ol+ynW+SvtcAhBPpVKpmtyUWqWxzqrWcd0aY2V+DcbisLMksQECEKhEYNbMmhtuYC3MfxFQ6RxivuXim3d/99KbHgq8e2HNpx+bf/HG3Ves3rhrmJm3IlAToBvpbrkr0urCVXa6MP0REV1HxJ9iktuP/uPPktCHiejdQvTaFl0g+/Et68+syS+AHR0dJlAzKwBbeMqE6BdEVLj8hclN6/bIS4OmzAL2AQ+xuwBlvpOcghhh0oL5XRWt3YNU/sEm91oFM2uIyHUGkWlZaHy85F3yeV2bflnx7KHpmvCijgLBgU5mE6zFo4kFWCQwDZpSyumih+Eo9x3JWp+aC7zfFCN6RTadHvAmJ79sAjW2lIrZJpWabXVtX461Rhq0tv8UAAACjSfgkgKNmd9BRPtsRuE6q8U2BZqIPCMi/8umD6ZMK6ZCW7NmTYyI1tsaFJQbfOCBB/YWbHN66/KZ8SsWkVv8167P2WzWXDh3TQt8byqVCrxZxrUvzVp+5cqVv0VEp9n2v5XWq/HH7JjW7dRkMvkq/1g8QwACEIhKoOiF3W9dddZ9qzeOfIGIryjXEBOt0qyGVm/c9TiTbNGsHhbS+2OkNGltLv6eKcznjHvpJIe8o6Nc+9gXLCBa7mHF5pe00IuoB7eCEqUEhGSj6+yzUnUFbdex2KtZgm/qKFyvJlevc9Aif1aJmVkTeFe/TbBm/vxFlMnMCiKXGzsr5ZoWbLo6xbxILMymDyh4UeEd0NYpAvOaNRfxCgNtebtnv9RKnVhw5/zsQtjS6ALBwRqkumv0cxjYP81cNM1Y/oGi9aLA79r8A8zrMiko40p9dWJiwsz+nLCZRVNYtXnPWj9ASr2r2L5y27RIHxNdVa6Mxb5fMvN1FuXKFhGRTxHR8WULld8ZST9ME5lM5iflm8JeCEAAArUXcAiq7BwcHNydSCRuY+a/tujpVCq0nTt3Hggqa1Kg2a4RwcyfHxoaeiSZTA4TUeDNpbnxfTyoD820f//+/X9MRC8J02cR+WyY4/KOYRF5e957m5cPDg0N7bIpWKwMM7+p2PaAbZsC9rfV7ng8foHL38aOgY2msDTr1nie/Z/buVRojzbF4NBJCECgaQSKBmtM72NH5q3Xc19YIcQvtxjNK4X4leZCMROTmFmASMdiwVb9IpNz6YmuNO0momT1W0MLBQL752XTdxZsq9pbFjnTpnIRmbFeTe4Y55k1Om9mjTCfFJQGxyYNWufk5Ena8buDRULf9TUVZLJBK1EmP2BVoki5zU4ziHIVOad8E62d0yaV6zT21UUg6E77rrr0Co1GKsBEh4MqFOZTg75rC+tgpUrOxpuYmHi6sLzr+8nJyceJyPxzesS7ui51OqBIYSG6Kzsx8YUiu5w2xbu6yq3XaFPX3kwE/bBpCGUgAAEI1FrAMQXa1Pep1vpzsVjsr3Ipgsp12ToVmkMKNBGRz5lGTWpPy3VMWioV2hlnnGFmmPxtOfgy+/YfPHjQpEMN/ejv718hImaWhvVDRD5jXbig4MDAQNzzvNUFm4Pe/mb+/Pn3BhVqp/3tvF6Nf57NujXJZPK/icjmOihprV9PRJ/wj8czBCAAgSgESgZr7rnuFYcuvemhPxDFO0ioJ4rGUEfNBX6+bd3y51fftPshYkGwpsb8wnTTpmtXHqlhs6+2aavIzJq5RDTH5tj8MvmBCsW8MOguHF3m7m6/Xq3Uqa6zQLRI6Jk1xLzQtT2/r+Y5dBq0BQsW0eRkye/f/DYKXjsHa5RSJwadm4I28LbxBIJm1pj/w3g0uwBz4M8LxXyS6//nir4jq2dqFoi+JILqTWrdSh9mRk2laQSfr7QTOB4CEIBAowqYdFaWP3ueHx8fv9uMY8eOHT/v7+//tohcFDSu3KyW24LKOaRA2zY8PDx1M0I8Ht/ked5NRBR4Y1ouFVpLzK5ZuHDh/xd2Vg0zf+Sxxx4LnO0bcL7WBewv3P2reDw+9dkp3GHzXmv9B66ptInom2HXx7HpUxOWMfcDXeDQ75Zbr8Yfu8u6NcycHBgYmIN0er4e0dDQkNW9ZStWrJgbj8fN9Y3jjh1d9tUfDw0NfalsidzORCIxwMzftSlrysRisRNSqVRube3yRyWTSXNTwp+WLzW9d/vQ0JDL/6vpA2v1or+//3Uisr1W7dWjHc/zDiaTjX1JXETOGx4enl5Co2y6oc3XLN+jRa8iIqRkqMcnqvI2Hz5ahfyg8qpQg6PA8yKToe8OcmzLL243s0apmTNrursD/3jxG5jxnD+zRiRwzRpWKmh2AInWzqnBWCmrnNgz+p57U6+ZNZ3pdJhZNcQhAlOideC5KWaDbY0jIETlgzVz5yLNZeOcrkp6ErhOjIg4f3copX5VSaeqcWzHnDlrQuSVL+zKhJdOT/9CW7jT9n1XV9fJtmXLlAtcb6jMsdgFAQhAoKEFHFKgfXFkZGTcH4yZ1eK/DnieSoVWroxJgUZE5oJ84IOZp9c9MRdQRcQq04HDOAP7UM8CAwMDvURT68KG6cbPnnvuuX8Nc6B/zMDAgEkz/Tb/veXzzZVc7BYRk/LN9XGH6wGtXH7lypXmWoL175mtuF6Nf34d07vNEcGN0b6dy3NHR8ebHQI1h8bHx7/mUn+1yjKzy6z+1+Vmp1arOxXXKyKBf4NW3AgqcBYoG6wxtW1dv/ypTpVZae48cK49/AH/Q8wPhj8cRxoBFpkK1jDxCERqK8AiN25d/9raXbyZN88sOm11walwZk1nNuu8Xo3RFOZjF5DNDJWAh7JYNFkxOy+eHQsRwPC7ykQVBTJY68D82n5b+c86FrP+RTj/OGF2D0xZnJv8NvC68QSCUgjOEXFdTLXxBokemZ/ZNrMzFrtSVfId6dqWbXkRMYtPV/owgZrA2UhBjXhKOd8kUFgnMwemsCs8Bu8hAAEINIOASwo0Zp4RnInFYibFlM3vrn4qtJIkJgWaTZBfRJ4ZHx+/J7+iwn7l7yt4PZUKrWBb0731PO9mIloQsuMfqnRWTTab/RMicknR+0JnZ+enQ/aXzj33XDNW1/VqfjY0NGR9133YvjXTcWa9Gpf+OgY0XKque1mzbo1LJ3Izu1wOQVmTpUTrsmuk5yOJyN35NwPk76v168HBwR1E9FPLdlkpdZll2boU8zzvhbo0jEbLClil4fn6VeeYi7J/uPqmXW8nJjM12Cn/aNkeHNtpVkb/DpHc2n3qU98c33/aV4jonGO7G/qVWYFsC4n8gJhNbthK02lEM1imqSDNveuXPbn65t0mcGA7vTCa9tu3lucm5kwtVlwzgXg2azWrxnQoyzxjZo1W6oRQqcBmzqxZGDTXdbKj4zmaLD+jXkywRsxXgf0jnU6HXrOGiAKDTOV6opQKFawRz1vMjmvz5PpRcu2JUv3MptMfIiLzr6kf8a4uc8dHZEEJIbrUS6dbIk91bt2RoP+CTXn+411d5rP7jxV3nvmj2YkJm4WOK26qyhU4B3onJiacvzeqOoa5c3tJT83arqgZJooiBRqJ550S8vt4uv9aBMGaaQ28gIC1QEaUNNzMP+vet0lBhxRoOwcHB3+Uz5JKpbKJROI2Zg78+RuUCs02BRozf35kZCST34+hoaHHk8nkMBEl8rcXe93sqdCSyeR7zHWbYmML2sbMmwcHB78aVK7cfrNWDjOvL1emcB8z37Z9+/ZjNwEWFgh4r5QyN4C4pgS+3VwrDqi6rXaLyIUuA3YNaLjUXe+yruvW5Gb9Nf3f27V0NzMAPc9zCRC6zGapxVBMfz5q05CIXJ4r63ahy6byCMp0dnYe9jxzSRuPRhIInFmT39kt15z9le4DXS8TYZOfb1f+vpCvzSdiiJnfrym2dMv6s9+wZX3f1zatXWu2nxWyzloetp9F/i4ey/72lvVnv2nLNX0fZZJra9mBcm3xpOyc2s8sRILZNeWwot33MbNWULRVBtZmtV4NEXl05MiM4IZoHSpgwXmBClbqcmI+r+y/F14I/CVcRFzvcDZ3VVdykayimTXpdDpUsEYxO19wNZ8AEZlx7gI/Fa1TYF6UgRrDkv/5bR2mlhxJqP8rsyREQv1fnVVPfTeYgJzrd6RJRzOdkqa+3T/aetzz/rfFgtOBXVVE3wosZFHArANkUaxsESY6VLYAdkIAAkZgn5CYRcs/RJrO7ZLjj9t5+SP/AprGFnBIDTZjVo0/Kq3158yvsP77Ms8lU6E5pEATETHtzXrYpmRzGO+sNuq9ob+//1VEZGbVhHk829HRYbsGQ8n6Fy5c+G4iWlKywOwdGa11pYuzm/V5XB7a8zykQMsTu+iii8xMKJcFHVp2vRqfxTHN26vPP/985wwhflvt+Ox5npltYnuz4ZPDw8MPNJJTLBYz6TVtfraZbp+WSCTObaT+5/dFa400aPkgDfLaamZNfl833XCGuTXe/BL0uTfc+MjLYyp7EbHqJxETXHlJftmC1yYAM0ZMPybi3axpx9x45+Cm950x60LrGzc8scCj8d8pOL6R3j7FxBs8mn/n1mtOn/HBPnzgN5+dd+LxHyCRl9a5wz/Z/OfLj92tZmbZCJ1X5z61fPNC9It52Ylar1Vj0uecKRYzNZho1EyuyT8RSqmFlouG5h9GyvMO+huyR45E8sOTiU7167R5FvOdUtmjkmCNuRvL+gJwR0fHWaSUWQPM/FR3unPJHyIr1Vh3yPsdq/bz3LkLSUd781tM6+dm/Eeo9hhQfygBFjnF5rstqHJhPvbzMKhwo+6fP38RZTJON9kI0TMNNxzmilOgCdFT6XT6ySjGNrUOkMXPz7JtMSNYUxYIO9tQwMxs2E1CO0XJzjjHdw5fNrKnDR2aesgOKdCeHx8fL7o4/I4dO37e39//bRG5KADDT4V2W2E5kwKNmQNnV4vItuHh4acLjzfv4/H4Js/zbiKioLU6p1Kh7dix46li9TTqtmQyeZKIfIOI5oToo2bmt2/fvr2i3xn6+vpMdpG/dGz/luHh4dDfDatWrUpqrU2QyuVxj/lcuhzQ6mXHx8fNsgfWs5McAxlNyZdL87bOtvPpdNqsqfVF2/IoR9Yp0JjZBFdtAyM1oU2lUqOJRGIbM9te1zHjNTM8G+6hlDqEmTUNd1rIOViTP4Rvv//M/yYi8+9Gs/2ijT/tEu/wYkV0vOqQuZ6w6vD0oYyKHzhy4MD+1A3nWV0by3YdfiWT0/WI/G5V7zXTGAv/3eEDv7691FjM9tUbd5mL9f9cvY7Y1Cwmj+L0g4keaqhvt+metdYLRfx/Nl27suIc+q4qwmw1s0aIZqRAM+2ISKiZNZPx+IGgtGau4yAzs8bhohmLPOvcxswDQo09V4V1oGaqvFKrhOhTM5t3e6e0bsuZNR3Z7Emiov2ZkO7oOEDpGbF2t5OB0jUREGartbgCO9MCM2s6JydP0g7fj8aERRoqwNvZ2XmGJrL6eRVwTiOZVWPaEObFtrf1leqT5XpDpQ7Hdgi0goCZNbODib9PmnZ08fG7Uu9KTbTCwNp5DA4p0L5Ybi2B3KyWoGCN+ZtkDRHNCtY4pEC7pdT5MovXJxKJO5n5mlJl/O3NlgrtnHPOManOTWrfUDeLMvO1g4OD9/vjD/vc3d1tLka+2OF48x3xDw7lZxUVkatnbQzYwMxhZx8F1Ny8u7XWLumoqJXXq/HPoknz5nIBO3fRHsEaH7DMc39//0oROb1MkfxdorU2s1ga7qGU+oJt+kDzc6yvr299uZ+V9Rrgs88+O75wYSWXxerV89Zut6JgTSHN1vVTs0xmXQwuLBf4XqlQv2gE1hu+gEkhskF16n/evG55YDoRJXqTZlXfYI3Q0RRouTFLVv+QYrHwAjgyWIBp8N6rln2ZnLL0BldrUcLcxfRKi3Lmwt3s/5/M4dasGR+fnllj07ZNGbNmjdNFM+ZKZtaY6d7dNv0qUcYtWFOiEpfNk11dv4w8QObSgTqVlVhsoetaRoFdPXy45ucvsE8oMFvApKhyXMdqdiWtkfZOK3Wys0WDzSjSSr3TeQzFTmhE69WYqk1ayjCzS2d0i3nWLPEZ+/EGAq0lgFkzrXU+S47GNiUYMxdNgeZXHIvF7vU8bx8RLfa3lXieSoW2c+fO6d/RTAq03B3rJQ45ullEnjly5Mg95Qrl+hkYrMmN26zT2xSPjo4OkzL2Y6azzNwlItMzJIq8NzNvpmffaK33Dg0NlT1/NggDAwPzPc/7sE3ZvDKfGRoaMp+LUI+BgYHTPM/7I8eDHx8cHPyu4zHtUNx2dsCURSuvV+Of7BDr1hhDcykD90j7iCWeRcR6Vg0R3V/J7LsSXYhkcyaT+Xo8HrddG3xBd3f3W4joS5E0HmEljz322GQy6ZIFMcLGUVVJgUiDNSVbcdzBJoWY492jjk1YFxeizTHRV22+Zrn19FxTdvXGXU8Q0SusG4q4oMRiqfwqt3zgNU+v3rjLXFwPmvqdfxhe2wt4pGPvo6n1gewPiqgks9avsakrE4/PmoliZtY4BUiONmRmD0V+xyQTOeV6FaLwd413d59IlSykVvs79TN06FDguj82n4NmKyNan1jpAuAzxsxsvguxit4MlAZ9I+KUGrHUKJTnTV/4KVWm0beL1ie7/j8Qov0NM67u7iXsee+I4C/YCS+dnvE7TiVjnEqDVkkFZoVirZEGrUJDHN7QApg109Cnpzqdc0iBtnNwcPBH5XqRSqWyiUTiNmb+63LlTLayjo6ON+fPrrFNgcbMnx8ZGTGBxJKPoaGhx5PJpElDkyhZ6OiOpkqFlkv9VjT9W8A4I9uttf5zcktn/etsNmu1OHepTnqe90Fzz0Wp/SW2mywHEfwqUqL2JtycSCTM9aE+h663/Ho1voVJ98bML/ffBzyfmkwmXzU0NPRoQLm23r1ixQoTTH6bA8IXHMrWtOjOnTuPJJPJu4jIdr0vE6RquGBNDs2suf2imgKisbICDRmsIeLfLtvr2ux8lkje+631fV8L0xwTDUv9gjU/+9ZVy35SpN8jROQ0xbVIHdhUTEB445ZrzvxxsV012DaZyWQetmonM/tvGMV8Qoi7iiOfVUNEZhH56TvBbMbDIqFn1nRmswtdUwrN6BNzrS/+VpRHekbfm+yNYl4Y5V9VUvtAW5OJN1R3K1783YxmsrMz+rSNNWZSzCe5/j9g5lkB+hp3mzo6OpYR87XieW8XIjMTtNKHCdREmW406E7v4P5iZk2wEUo0iwBmzTTLmapyPx1SoFnNytBafy4Wi/1V0ILShanQLFOgiYiYNXUDHyYlGzMHBWvMGjcmJVvTzK4JHHgVC6xYsaJHREywxuXx4fwZVC4HmrLJZNL87Ha5O98ctu/AgQMNmU7JdfxRlldKnSci1kGvdlivxvd1XbcmlwoNwRofsMizCciLiEndaPM4ND4+Hup6rE3lUZRhZpMKzTZY8zpzI0SDzhRCfvgoPhAR1mH9pRxhm8FVMfUEF6pmCdmS6Yj93paQgRrTM01U9g6javaeiP6zRP0mWINH9AJPqjle0J1i0bcaUY0h16yJPFjT1dXlfAc9KxX6QqRWqqLEnFzrC/7ModMERPRRqVs1InJilI0zc1vOUIrSsEZ1LSAik66w8kcLpL0zaSKdISpf18u5ydwBKtbVdUm8q+t+UWq3MP8xRROoMfkltobtVInjTPqYih6MYE1Ffji4rgJm1sx/ENGHSNO5XXL8cTuvePicne96+P3fv/yRu4YvG7HOLFDXUaDxyAUsU6A9Pz4+frdN42ZBd2b+tkXZqVRoppxJgUZEZtHusg8R2ZabXVK2nNkZj8c3EVHg3zGW4w9srx0KxGKxT+ZuurMd7lMHDhz4tG3hYuVE5Lr8dG7FyhTZ9imT7qfI9rbeJCJON/O2w3o1/gfCNd2b1vr1/rF4Li6gtbYOsorI3Y24xkv+yAYHB81a4T/N31bmNSulLiuzv567zBjM9SYzw6bYP6R8rvHZadCZNVTRRdQKDDNMcu29V5/96UrTWSmhxyREbqkK+p53qHwn782xl8wjEeWKP1YnXmkl+l02axk1LFW4NWsin1WilTqJtHZi0hXMrBGtF7mmFMrvnNT2gv8vSevN+e231WvmaH8m1DrQ1lYnK7rBmgBuRLnqTIqqbHQ9q09NInKy668VIlLrNGjdHV1dlwvR+4noZdWQUkTfirBeQ1p5sMbzfh1hn1AVBKouIERfiqvYXyEYU3XqpmzAIQXaF10upJlZLUR0UQDKdCo0hxRotwTUOb07lUpNJBKJO5k5aO2apkqFNj3AGr9YtWrVhVrrtS7NMvO1lQRNcrNq1rm0SUTPxWKx/+d4TLsUx3o1Jc6067o1zJwcGBiYY75nSlTZ1psHBgZ6Pc9zCQ42bAq0ghNp+mmV1lFELs+VdU2YUNBktG+HhoYCZ5yWa9HcXJHNZkv9qTrf3CtR4vg5k5OT0+uo5Zfp6Ojo8DzPZN+Z9WDmZURk0lpaPUTkUiJq6IBTPB6fkS2pFJjVgKtYKNK7qC37uV+JXrP5muXD0SwQz3vqlA7VS3fJ9mJjVtp7UHNjTqYq1t+m2Mbyyc3rl5vcx037CLlmTeTBmsyRIz/u6Og4ywUym8k86VI+v6xSamGI9G/HqhCp5uwMk+LHpPrZpkS2TU5Ompl6DfUD/RhE9V+xyEkS4TpmmFlT/XMWRQueUotcA7jF2hWiXxXb3mzbOERQgZlrM/bu7iVxrd9HRO8NOVvT6nQI0VPpdDr09/6sRubPX0SZTMW/GCmlsGbNLFxsaGCBH3P33CuH1+6MMp1gAw8XXXMVsE2BxsxWKdD89mOx2L2e55k7d8umn/RTodmkQBORZ44cOXKP34bNc67fQcEapEILwDQXpT3Pc50hc+/g4KDT+SrSjb90nVXDzP+cSqUa+kJdkXFWfdPKlSt/i4hOc2iobdar8U0c162ZIyJmpfb7/OPxfEzA8zwzq6TUBf1jBY++enJ4ePiBwo2N+D4Wi93ped5HLMd2WiKROHd4eLipryEWnodt27aZ2TilHpHf1JZIJMjlxut4PD6cSqUi70epAUexveI/UKPoRJE6ah2s2ZX19NlTgZoinQmzaa53ZDTMcZUfw5nm34sAACAASURBVDu3rVte9D/K5muWm1QGtblwU/lAmqGGES3HNW36Mx+Yzcwax0eV1vw4bNbecflXSXRctK5otkbEF/w1Mf+AmD9KzOdl0+njs+n0xdl0+pOTk5Mm723bBmrMR1MinlmjMbPG8X98fYqL57mn/SrSVa79+lJFehHBJpGyF7eKtcBaV3WtK7MeTUdn551xz/sZifwliVT0vVpsDAXbopxVQ52Tk5GsiZSOx3EBqOBE4W3DCrxAEluzE4Gahj1BjdAxyxRgOwcHB53SfqdSqayI3GYxxvMHBgZeYpMCjZk/PzIyMntRzjKNDA0NPU5EgRfKLB3KtNTauzzP+3siOt1hlBPMvN6h/KyiAwMDJrDgPKtGKfUvsyrDBhOQdJnlQO20Xo3/8XBN+6a1Dkzd6Nfdhs/WKdCY+Y5muQaSSqVGTTpOh/Np7eBQJ4q2mECjzqyxXXAqitOxLXak+y1brntFpHdFbrp25ZHVG3e94Ji/NYLxyDcCKjHr1iCXZgCSxe6Dnsdv/fYHTm/+hbhEnIM1LXHx06xZI+FjIJVe8Bcic3f4fSSyzZuc/K5N/myLz2VrFjFr1kQ5s6Z+63i05vmxG1V3V1dXr9Z6gcRix4nWLyKljlMix4nIAlJqgVlsUoksEGaTo/5FQmTu9qv80SrBOWbndF2Zjo5fUsbpGpaVd6yrazUTfVCIzrM6ILpCka5Xo5U6uZKfA9PDeuEFBGumMfCikQWY5b07rhh5opH7iL7VV8AhBZrTrBp/VFrrz8Visb8KuAM5ns1m/5qZO/3jSjyLiHyuxL6ym01KNmYOSvuCVGglFFetWvUarfW1JXaX2vzhwcHB/ym102a753kfC7EG3gbMqimui/VqirvkbzXr1nieU2JmE6z5UH4deE3U39+/UkRsg7uitb6zmdyUUl8QEauUgmbWaF9f33qXNKLNZIG+RiPQqMGamsz4EaK75h3oumzTDa+o1kJzv6l5sMbzvl7+oyEjRIxgTXmkoL3Cwu/89gfO+llQwSbYbwI1tlNRjw1HJHBhzmOFG/OVWbTefeDHxuIasNLMBxWRWYT1vhjRtomJiVb4/BwDqeariGfWuJ67ag6tXeqOdXZe6hF9hZQic3F8atqyyNEpYyYQZ7YdnUU1TVLJ/8/pSswXXKvMrGE+yTmwMD5eldm0TPRNIorlO9fg9YSXTpv0kJE9ROuTXabQl2jYRP3NzTl4QCBIwPy98TgJPSIsjzApM3P2JUThLjYHNTZ7v9y24/JHvjR7O7ZA4JjA8PCwycQQ1Y/gYxXnXu3YsePnRGT7t/57ZlUQ0Ybh4eEvEpH5h4ejQC79mVmjwfY8mt/FHlZK/ZNjUzOKn3vuua8lorfO2Bj85hfZbBazaoo7mf/nTjNrTOCieFWtu9V13RoievX5559/yvbt26s6u73ZxEXEZTbJ/bmfRU0zzEwm8/V4PG6u/9pMPFjQ3d39FiLC72RNc4Zr39GGC9asufvu2HgNlsNloS93L37ysk3r1zqFyV1OEZP8Roid05a4tFFQdteWD7zm6YJthW/NzBo8KhO44d5rzoo0FUtl3Ql/dFdX18Iw/wFa4eInE1WUroe1dlq3x5uYuMMjMtN5Kfr73MN/BpriSJNaKcKZNZXOimoKswbrpGJeFH4eW2WDaZHz3UmusyCPrqsV/dfN/PknUSZT60CN+RCYCwSRrrER0efS/GGGBwQKBfYRmYAMPypCj3BMP9r54oVPpM5LZfMLrrh92R9W77J4fkv0Y+ruvnrGFryBAAQgEEJAa72BiF7pcKj5c/PdJg2ewzGFRVkpdVPhxqD3zPw3O3difa5iTitXrjyT3NZDbLv1anw3x3VrKJ1Om9k1CAbnAFesWDGXiN7me1o8m2BwUz3M90wymbyLiP7UsuMmeIVgjSVWOxZruGBNZuz0BRSr+iWdr841gZq11QvUmA+TEE/U8kMlxF8Jao+zsQclroOKYX9JAfm3LVef/fdUUbbdkpXXfIfW+oSpO90dW9YtMLOGiCpaGysWix3IVCG9kOOpaIfiTMwVnatCpIjXGyqsHu+LCAjzqc6zQorUE2ZTKwSXqbt7EbmlYDBTiqoyq6ZzcnKRjjB4anlO/4uYK7ojt1g7kXwumXXHnDkudwsW6wopkeF0Om3SY+LRXAKzZstMdqpHRv73SFX+/4WkwTo1IeFwGAQgMFPg3HPPvUhEXP8S/ofBwcHdM2tye5dMJi8not93OcrM5hkcHMQF8xJoZr0acUgJ3o7r1fh0uXVrrNdKYmaTDgufvRxgR0fHm026a98z4PnQ+Pj41wLKNORuZjap0GyDNa8zaUebbQZRQ8K3aKcaLliz7Pllv/nhwop+lpc9VUx0/9wDXe+o5oyash2o3k5RWf5yUPX3XrtsbPXGXWZKZiQLNwe110r7heQ78w7MeTcxVz2aWCs3Meu2hHgwc9OnQas0WDMxMdFIF2JCnMUmOWTBgoU0GW2mStdZUU0i1dDdFJGTqpZTJWDkLNL0/1c7MplTxKSQc3s861bcrnRk67zYNbddiD7ppdNmrZrIf/ZG8rkUOUGIbrcbTulSmvlddHQts9KFsKfeAlazZerdycL2sU5NoQjeQ8BeIJFIJLjEmnHM/HsuF7vtW23MkgMDA6d6nud6x/vI+Pj431cyooGBgeM9zzOzeVwf1xBR6LtUBwYG5k9OTp5WptH5ZfY1/C7b9TX8gTDzZDKZ/EP/fTs9M/OLHP+vm2CN+dMn8t9d6+Q+P5FIDMRiMS+TyRyKx+OeUuqQ1nrq+dChQy+MjIyUnM2vtb7CNu2wiNzdrGu5DA4O7kgmkz8lIpu1ecxswcuI6CO1Pqd9fX0d3d3dq2vdbpTtuf781VqvTiaTTZW2uuGCNTfcwHr1xl1Rnsf8up6Ie/xHm244I9orf/kt1Ok1E33XBGKsmmcaIaGLrcqi0FEB5gdjnfrNrfbZEZETbH9w5n8UWuRid6hAVc7BTOdH6pv8D0WVXndNTp4YJlVfue7EYrHnMCuqnFD0+5jopOhrtatRMz9nV7JxS4lSJ4foXVWSyorWp4T5ueHQ/wyLfIWJ/nlyctKs6VG1B7ul/6haP1Bxwwk0w2wZSzSsU2MJhWIQKCrAzOZC2qpiOx0v3haromm2rVmzJrZ///5/IyKX30cmYrHYO8tdxLUB8DzvHx3bNdXeNTg4OGhTf6ky2Wx2eSwW+26p/c28/aKLLuo6fPhw0nEMf0ZE5l/bPUL8Xz81mUy+amhoqKq/x9bwRPwOM39Xa02xWIyMh5eb8W+eu7u730xE3yjWn4GBgV7P81zWRnINCBdrtp7bTP8/atMBETEzBk3Zmgb1FixYMM8LXOvcZgT1K+P6f1JEmi7lXMMFa3Kn2+QkN3kNo3w8L0q96Rvrl/06ykobpS7NfJt1XzSNECNYY+1F9IN0p/f6beuWjzsc0xRFFfPCMD8ZlFKtMLOmkmCN03o1TfFhaNBOajP7S4e+Ka7oqDArqihLdTeKnBrlukNOnRVp+v+vIrLINUAiRFWZURTROi+zT+HRGZu3ZJW6mcbH984uUJUtp1alVlTaTAJNOVvGEhjr1FhCoRgEIFBe4Jlnnvk7Inpd+VKz9q5PpVJPzNrqsMHMbHJYA8Kv+Tda62v9N3ieLTA+Pr6yCtfbZjfUxltyqdBaJVgT+kx6nmdmj9gmWHhyeHj4gdCNNcCBsVjsTs/zTJDfZsynJRKJc4eHh4cboOvoQoMJNGqwxlwUjzRYo5iv2HzVsp/U2P/4GrX3nMj8/7BuS9FDtY3dWvesEQtuV136ja0YqDHYotQjJGJ++XZ6pCcmanUhzalfDoXN98sch/KFRZv+Tv3CATXqe631iTa/6Tj030zRPuRQHkWjECiRQiSKqoPqYKWaPljDzIuDxlm4n5lNytPIH5Gs85LXKyF6WhF9KjMxYe5EO5y3qxYv6zbjqxaDQxszBFpotsyMcZV6g3VqSslgOwQg4CTQ39//RhH5K5eDTCqj4eHhf3U5prBsbvbHrYXbLd5f98ADDzT736oWwwxfRGvtMtMhfENtfKTW+vVE9Ik2JvCHbr2uIzPfUetZJn4no3pOpVKjiURiWy5YZ1Ot8UGwxkaqzco0arDGXAiNbkFpkc9sXn920Wl5rXC+heiOretPT9uOJZvVP4zHnHPf21bfSuX+vftA1xWtlvos/wRljxzZQUTmX3s95s49saLZGi1wp37TnHDmhREvTN/0F+6b5tzN7KhL2oyZR1b4Lqb1gWyFddT9cBPsclgE1vSXRX5ZjX5Hss7L0Y49ICKf9CYnv+FVkFO+ojGKLKrbjK+KOo6D8wRM8H1B3vvpl0z8CxG5nmP60c4XL3widV6q6b8KpgcX8ALr1AQAYTcEIGAlkEgkXiYid1oVPlboyUwmY7vI9rGjCl4dPnz4OiL63YLNQW93DA0N3RJUCPvJrKmCRxUFmDk5MDAwJ5VKTVSxmYauur+/f6WI2KzfYsYhWmvX75qGHL9S6gu2a0Ix89q+vr71zbpOT0OegBbpVKNesY/yrvUn1Rz5UJ3OVy1m1gh73qddxvefH1i+j4hwt0l5tA9vufqsd7RyoKb88Ft7b6fnVZICjYgZF/xr9BFR5mJqtA+cu2g9bWrrJKJa/Dws2pd0R0fTn3PR2jnYpUWeLQpS4cYK13nxmHkTK/XabDqd8CYnv1bJ4r8VDiVOzNHdGFRhZ3B4OAEW+mCpI4XkxaLo9B2XPfrjdgrUEGGdmlKfCWyHAATsBRKJhFnb9B4iepH9UTTOzG958MEHK1rbs7+//1VE5DSbh4jMDEoTJAqT5dthiM1d1JxXIupr7lE0Re/niIjrukBNMTDbToqI9awaIrp/eHh4j23djVwuk8l83WF94wXd3d1vaeTxoG/1EWjIYA1LlIsBy7s312+tkeOqfVpZ6GtbPvCap13bEaIR12PapPyvielNW9af/bfEjF/0WvSka6UqCgCwSJQB5RZVjmZYEv3FVJy7aE6NfS3d3RX9f7NvqETJw4ebPljDzKeUGF3JzaxUVdKgEZFzSrZcerMb48ynZSYm1maOHHmwZMdrtaO7GynQamVdxXZ2XPHw55jovlJNsNANK+5Ydk2p/S24HevUtOBJxZAgUGuBM844o5OZv0pEL3dpW0TeMzg4+COXYwrLmrZF5ItEZG72cXl8ZGho6HGXA9qxrFLqPCJqyOuArXY+tNZ/0Gpjsh3PihUrTNr5t9mWJyKTDrklHjt37jRrsN/lMBiXoJZDtSjazAIN+SUtLGNRoIrw7VvW9w1FUZdrHas/86i5YyHipRZm98JT/KnZW4O3MNFDwaXarsQOUbRsy9VnmzuI8GhhAdG6opk1wlEGlFsYOoKhiUhF56pIFxCsKYJSzU0dmYxzoCGC/pi7Kx8WIpPr3IugvvpWEWLNH6V1VWbWEJFL8G2UiP4im073ZtPpD0xMTPysvpDHWu/MZhGsOcbRvK/YLL8Xe0/ZtciEbnzt7cva4Q9hrFPTvJ9k9BwCDSWwcOFCk7njdS6dEpGPDA8P/7vLMcXKLly48AYiOrPYvjLbdpx66qn/UGY/duUERATr1dTu09C2wZqOjo43E5HtzeuHxsfHzWz7lnkws0vw6XWJRGJpywweA4lEoCHXrBGmn0Uwp+GFbKe6PhKlMJWk0ydQLBbmSOtjhOh7W68+6wHrA2YU5BHMEJ4GMZHvv+k+9ckbN61d2/wX9aaHhRelBJRSC8Vx/YcZdWHNmhkc1XyjmE+s6FwVdE6IflWwCW+rLCBKOafwcukSE/1ciH5EzD8SrR+NET06OTn5EyJqmfUpWOQU16mek11dz9KkiVlF/GA+OXD9HOYR0fpT3uSkuausIc+DDjFbKWJJVBeRwPBlI3tW3r7sg8JTwdmitTLTbSu+sOyPSI4Fb0VRB2uaV/SAWm1kp+BnUK9eIPI+u+L2ZUHlsB8CEIBASYFkMvkXRGSC4C6PbwwPD/9flwOKlV21atUKrbVZq8blcVhE/njTpk34O95ODevV2DlFUerV559//inbt2+v1mz3KPpYlTq01lcw2927LiJ3t9qaLYODgzuSyeRPichmzR5WSl1GRB+pyslApU0p0JDBGtb0s0rnpAjzP33nz86syuK6NmeaYx2LhLRN0dBlFLO56yTUI6bjD3kqE+rYVjpISL4R4/i1m68+839aaVwYS3mBqZk1lr88FKuJsWZNMZaqbIt6Zg0TNX1KrKpAV7FSEVlk+8t6QDfMQuKPmsCMIvqRKPVo9sgRk2rj+fzjWvEvdSFyDXh5dOhQNQKTHSRiZg4Xe5h40r3E/InsxMT3ihVopG0Rfi4baVht2xeTDm3lHcvWCJVcNNlkE7gk/++LqRvD7K4jNIvrycTO3xXNMjb0EwIQqIFAIpEwFww3ODY1Mnfu3HdWulbMwMDA8Z7nfdk1RRczXzU0NOScFt5xjC1RfOXKlb9FRKe1xGCaZBDpdNrMrjFp/drmMTAw0Ot5nssMLpdZKM3kaMb1UZsOi8jlubKu9+fZVI8yTSjQkGnQmFWlP2x/PU91fqKe50NYn1rN9s2smnuvPisVto173v+qZ4ToF2GPb/rjmB9k5vO+tb7vzQjUNP3ZdB9AheugaMyscTcPf0S0C4BjvaHwZyLkkczsusaJibf8FzPfTSJ/I0RvijP/djadPm5qUfp0+s8y6fRnskeODBcGakJ2sdEPM3f+m7zPLo/qpEArvs7LhBB9Nkb0u9l0+o3NEKgxkAoza1w+T41f1iYdWuOPAj2EAAQgUDeB/v7+i5n5c44deMrzvIu/853vvOB43Kzinuf9KxG9ZNaOMhuY+fODg4N3lCmCXXkC8Xjc5QJ63pF4GVaAmdtuJpPneSboa3s7zJPDw8MhswWFPSu1OS4Wi93pEMQ+LZFInFubnqGVZhBoyJk1Hk08oZzXkzvGzSI3bXrfGYePban9KyZaUs2QqJBUnOKNmR8ikRfXXqeuLW5nUv9479XLvlPXXqDxugqY2RqV3OnPSmHdkxqdQSZaFOV3KSuFmTU1OnfTzZj1VkqnHTRpAczsmEeZ+UfkeY9kMpn/IqKJ6eNbYtGZ/NE4v84Ss1kM1vrBzCa9Z+SPjkzmZFHT9/n8kkRuznZ1fdbM4mm2GU1ik84tckFUWE0Bm3Ro1WwfdUMAAhBoVoFVq1adp7X+KhF12I6BmceUUm8YGhqqOJtJf3//+0TkrbZt58rtymQyVzke09bFsV5NXU6/CdaYwEWUf9LWZSAOjVqvE8jMJtjakjapVGo0kUhscwjYGTdzMyIeEKCGDNZsXf/a36zeuOvnRGSmabo+Jj1msyBeXR+iaYl1LNmxpyz05a3X9H3f8bDZxbUeIWaz8FerP35FTP+uhT67df3Zj7f6YDG+YAGucGYNex4u+AczR1JCiCKdWaO1xrmL5MzYVyJan8TMJvjyuIg8qpgfFeZHs/H4j+jw4Yr/wLfvSdOWTGcnJkLPpI1y1KLUKUT0GDN/MjMx8W9ElK7KujhRdrpEXVNp0Ersw+bmFbBIh9a8g0PPIVBGYGhoyPYu5jK1YFehwNDQ0EDhtlZ8f/jw4QcXLFiwxGVs6XQ6vXPnzkhuDlFKmQu25vcK68fcuXOPbN26NW19gGPBeDxuLpqWSv3qVJuxcjqgSoWHhob+FxGZf3i0ucDg4KBZUiH0sgrl+IaGhl5Wbn8t9g0PD5u/ner+c3F4eNikwWuoRyqVen5gYCCS77aGGliLdaYhgzVTxkyPkbgHa4ToK1vXn12d9B8uJ5/l1Cp9N0x4HHNddK9oz4VopO7fXkV7VvlGk+KNmbeK1l9/Zo5sH1m3HAv0VM7aMjXEiP5cax36l5NMJoOgX40+Dax1pNOBs5nMkzXqOprJCXidnf+HDh++0p8g02wzMHAijwlk0+khInpVK9wB5zF/tMPzPnNsdPV9lclk9tS3By3SukmHdmfsPZ72fkxEC1pkVBgGBCAAgaoK5Bb3Hq9qI2UqT6VSdc2KUqxrqVQqS0S/LrYP2yAAAQg0sYCkUil8tzX4CWzVa/UNzo7uQQACEIAABCAAAQhAAALVEFh5+7I/FaZbq1E36mwQAaGbdr7r4fc3SG/QDQhAAAIQgAAEIAABCEQi0LgzayIZHiqBAAQgAAEIQAACEIAABNpJIJcObZVm+r1GHjcLvchhQW0tPLXGVyMPqWZ9Y6GxmjWGhiAAAQhAAAIQgAAEIFAjAcysqRE0moEABCAAAQhAAAIQgAAEIOALrLh92R8S09f992WetRBd9v0rHnZa06FMfdgFAQhAAAIQgAAEIAABCDSggGrAPqFLEIAABCAAAQhAAAIQgAAEIECEQA0+BRCAAAQgAAEIQAACEGgTAQRr2uREY5gQgAAEIAABCEAAAhCAQFMJIFDTVKcLnYUABCAAAQhAAAIQgEBlAgjWVOaHoyEAAQhAAAIQgAAEIAABCEQtgEBN1KKoDwIQgAAEIAABCEAAAg0ugGBNg58gdA8CEIAABCAAAQhAAAIQaCsBBGra6nRjsBCAAAQgAAEIQAACEDgqgGANPgkQgAAEIAABCEAAAhCAAAQaQwCBmsY4D+gFBCAAAQhAAAIQgAAEai6AYE3NydEgBCAAAQhAAAIQgAAEIACBWQII1MwiwQYIQAACEIAABCAAAQi0jwCCNe1zrjFSCEAAAhCAAAQgAAEIQKAxBTIs/I7vX/HwvzVm99ArCEAAAhCAAAQgAAEIQKDaAvFqN4D6IQABCEAAAhCAAAQgAAEIQKCkQEaI37rzXbvvKVkCOyAAAQhAAAIQgAAEIACBlhfAzJqWP8UYIAQgAAEIQAACEIAABCDQoAJTgZrvX4FATYOeH3QLAhCAAAQgAAEIQAACNRNAsKZm1GgIAhCAAAQgAAEIQAACEIDAUQFFNGlm1CBQg08EBCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAARyAgwJCEAAAhCAAAQgAAEIQAACtRTo7e29jogOjo6O3lrLdoPaWrJkyQVKqT6/3Ojo6Ab/NZ4hAAEIQAACEIAABCAAAQhUUwDBmmrqom4IQAACEIAABCAAAQjUQaC3t/dKrfVL9+7de32p5pcsWfJxpdRBrfXI3r17t5UqF/V2ExBh5vty9T6ttV67b9++kajbCVOfCSKJyMf9Y8fGxury95Ix8vtQ6XMtz22lfcXxEIAABCAAAQhAAAIQaGeBeDsPHmOHAAQgAAEIQAACEIBAowr09PSIQ9+2jY2NXbh06dITPM97SEReysy0ZMkSKhawWbp06Us9zzOBCTLlenp61o6NjW1yaC9U0cWLF/cx893+wcx8sKOj42n/PZ6PCuQFs6IgqUvAKYqOow4IQAACEIAABCAAAQi0kwCCNe10tjFWCEAAAhCAAAQgAIGWFtizZ8/Bnp4eM5tmKiDCzNf19PSMFAZiTKAmD8IEemoSqFFKmRk1J+S1XbOXudRrU+0ppTbt2bOnoiBRfn21np1UMzQ0BAEIQAACEIAABCAAAQjUTADBmppRoyEIQAACEIAABCAAAQg4CZjUZC/N/TMHFqYq81NlPS0i02nETOClt7f3+rx0XrcsXbp0mwnkmEpys2qu9HsSi8XW+a+r9Wxm1BQL1IhIn9b6vqVLl66tNHgS1Pc8D8pms8aromBNfn1KKRMgKzw/QV2y3e9ULzOfYFxtK0c5CEAAAhCAAAQgAAEIQKAxBBCsaYzzgF5AAAIQgAAEIAABCEBghoBJa5a/hop5n1/AT5PGzLeOjY1tyN83Ojq6oaenxwRzzD+TGs2swzIVlPE87xa/LDNfX+0gSW6NGjPTx59Rc5CZN/jBDhNYMKnblixZshbrq/hn5thz4Xk/tqf4q4I1gYoXwlYIQAACEIAABCAAAQhAoOEEVMP1CB2CAAQgAAEIQAACEIAABCoWyM2YedoEZGKxmJn5Qb29vWZGjT8jZ5sJ6lTcUJkKTLApE3mQ8gAADApJREFUt/7KdKBGa32haZeZTfBoaraPCeSYcvmpxcpUi10QgAAEIAABCEAAAhCAAARaTgAza1rulGJAEIAABCAAAQhAAALtKuDPtjHj9zxvisHMYDEza3p6ekhE8mkuyC9vgjpRBW9yqdZuERE/MGTaPWgCNfv27ZtK2TY6Onrr4sWLR/LTo5m+9vb2rvE8b51fLr/DeA0BCEAAAhCAAAQgAAEIQKBVBRCsadUzi3FBAAIQgAAEIAABCLSUQOGsk4LAS8OM1czeyaVd82fTEDOPFAvAmIDM0qVLf8fzPJMmbSqwY9KiKaVMWrQN8Xh8g7/WTsMMEB2BAAQgAAEIQAACEIAABCBQBQEEa6qAiiohAAEIQAACEIAABCAQtYC/xktAvaUWo8+f4VKqjJ+SLKCJ4rvNWilKqY8XWdx+k1Jq3ejoaNH6c8GYGevzmBaY+TrP867s7e3doJS6FUGb4u7YCgEIQAACEIAABCAAAQi0hgCCNa1xHjEKCEAAAhCAAAQgAAEIUKnF6PPTnZUqE5Yvt6D9dWZmTMFsn4PMvME2tZopt3jx4m2xWMykT+vL9eeEXBq365YsWXJrPB43QZunw/a1GY/LP3fN2H/0GQIQgAAEIAABCEAAAhCwE0Cwxs4JpSAAAQhAAAIQgAAEIFBXgbGxMc7vQL0v4pt0ZyKyxk9flt+33OupQEtPT8/Hi+wruSkX8PFn4fip1E7IzbQxQZsNe/fuvb5kBdgBAQhAAAIQgAAEIAABCECgCQUQrGnCk4YuQwACEIAABCAAAQhAoN4Cudkv+enVTJeeFpFNJrBSYf9GYrHY2tzaN1fm1XXQzK7Jex/qJTPf19PTM+vYgplBVO+A2KwOYgMEIAABCEAAAhCAAAQg0LICCNa07KnFwCAAAQhAAAIQgAAEIFA9gbGxsXU9PT1m5ouZXTOd8mzx4sV9zOynMQvVAREZya1Rs27p0qUbPM8zwR8zk2dtO6RBK5xFFQoRB0EAAhCAAAQgAAEIQAACTSWAYE1TnS50FgIQgAAEIAABCEAAAo0jEIvF1mmtR5RSZi2ZqdRl+/btGyGiC6PqZS44MxW0aYdATVRuqAcCEIAABCAAAQhAAAIQaC4BBGua63yhtxCAAAQgAAEIQAACbSrQ09NzX7mhB+33jy1Xjpk3jY6OWqcZywVoNvh1V/O50kCNzWyV3t7e60Rkeo0dm2OqOWbUDQEIQAACEIAABCAAAQi0jwCCNe1zrjFSCEAAAhCAAAQgAIHmFihcH6ZwNEH7/fLlym3zC+G5NgImbZxSajpAFNSqSRG3d+/e6/1y5YJvfpn8Z9eAXP6xeA0BCEAAAhCAAAQgAAEIVE8AwZrq2aJmCEAAAhCAAAQgAAEIRClQGEgpF3SJsl3rulwDBzYVj42NVZRSrZqzZXp6esQfAzNfPzo66jzLiJnNuj/W55KZ/Sb9Z+tjcwcUfo78evAMAQhAAAIQgAAEIAABCNRRAMGaOuKjaQhAAAIQgAAEIAABCNgKFAYt8gMFpo5SKbsKghUHx8bGFtq2GaKca+AgRBM4BAIQgAAEIAABCEAAAhCAQOsJIFjTeucUI4IABCAAAQhAAAIQgMC0gIi8dPoN0Qm9vb1XuqxLk3csXlZZgJlHtNbTKc785pRSfflr6fjbC59FpOgsJGZeQ0RXFpbHewhAAAIQgAAEIAABCECgcQQQrGmcc4GeQAACEIAABCAAAQhAoBoC5kL99ENEzPtbpzdU6UWpmT5BzS1ZsuQCZr4vqFwr7heRg3v37p2VpmzJkiVUJP3ZLIJix5pCvb29Jtgzqzw2QAACEIAABCAAAQhAAAKNI6AapyvoCQQgAAEIQAACEIAABCBgI7B06VKzzsnUQ0QuMGvF9PT0PJW/3ew0s2iIaLps7pALTEAk9xpPEIAABCAAAQhAAAIQgAAEINAAAphZ0wAnAV2AAAQgAAEIQAACEIBAkMCSJUs+zsx9RNTneV5+AGY68JLNZs3+6ZkZInJdXr1m+1RZpdTHiWh53j68hAAEIAABCEAAAhCAAAQgAIE6CmBmTR3x0TQEIAABCEAAAhCAAASKCZiZLz09PQfy1ylhZhN4McGW/EDN9OFmvROTRsvf0Nvba8pPr1cTi8XW+YEcEenL7feL4xkCEIAABCAAAQhAAAIQgAAE6iiAYE0d8dE0BCAAAQhAAAIQgAAEignkgi5FgzJEZAIy+bNnNpj1YUZHR5fv27dvxNRngj35gR4R2bBnz56nzbPfntmfS5Pmb8IzBCAAAQhAAAIQgAAEIAABCNRJAMGaOsGjWQhAAAIQgAAEIAABCJQSyAVdDprZMkR0KzNfLyIXxmKxhWNjY+bfhf6xSqnp2TRm2+LFi/uY+W5/vwnuxOPxqSCNWYC+IGBzS09Pz5q8sngJAQhAAAIQgAAEIAABCEAAAnUQwJo1dUBHkxCAAAQgAAEIQAACEAgSMEGZoDKF+02gRil1X36qNBFZu2fPnumAjgncaK3NzBuzvo153N3b23v96Ojo9Kyb3PaKnnp6eqSiCqp0cLl+iczscrmyVeqeSX83sxMODZU6tnBcDlWiKAQgAAEIQAACEIAABCBQIwHMrKkRNJqBAAQgAAEIQAACEIBANQXMGjRKqYfyAzXMvM7Mpslv1wRulFJmZs50AMekROvp6bnPpE/LL4vXEIAABCAAAQhAAAIQgAAEIFAbAcysqY0zWoEABCAAAQhAAAIQgEBVBLTWJ5hAi4jMCLSYQM3o6OitxRo1AZulS5cu11rfnTfD5gJmfjp/PZxixzpsmxEksj2OmU/I65PtYSgHAQhAAAIQgAAEIAABCECgqQUQrGnq04fOQwACEIAABCAAAQi0u4BZs0ZrvYGZTVqzE8yMGa31hbl1b0ry7Nmz5+mlS5de6Hnex4noSiLaNDY2tq7kAY478tfVcTnUzO5hZpPKLZJHLr1bpCne/I6VSjvm7w/xvK2Ym63J2NgYF2vTzLoys6eK7cM2CEAAAhCAAAQgAAEIQKAxBBCsaYzzgF5AAAIQgAAEIAABCEDASYCZrzcHaK1HTKqzxYsXX6iUui4Wi60bGxubTnFWrtLcWjbrlixZsikej4+UK2uzz++TTdlSZUw/stmsSdPWDI/82UNW5oWDEpGDzDxVj4gUPQfxePxprfXU+c5PX5erK78PhdVPvTefEaXU9OelaCFshAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQKCRBP5/Qr/OT+0bbJUAAAAASUVORK5CYII="
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![image.png](attachment:image.png)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}
